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SPIRES-BOOKS: FIND KEYWORD MONTE CARLO METHOD *END*INIT* use /tmp/qspiwww.webspi1/9692.165 QRY 131.225.70.96 . find keyword monte carlo method ( in books using www Cover
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Call number:9789811033070:ONLINE Show nearby items on shelf
Title:Monte-Carlo Simulation-Based Statistical Modeling
Author(s):
Date:2017
Size:1 online resource (XX, 430 p. 64 illus., 33 illus. in color p.)
Contents:Part 1: Monte-Carlo Techniques -- 1. Overview of Monte-Carlo Techniques -- 2. On Improving the Efficiency of the Monte-Carlo Methods Using Ranked Simulated Approach -- 3. Joint generation of Different Types of Data with Specified
Marginal and Association Structures for Simulation Purposes -- 4. Quantifying the Uncertainty in Optimal Experimental Schemes via Monte-Carlo Simulations -- 5. Normal and Non-normal Data Simulations for the Evaluation of Two-sample
Location Tests -- 6. Understanding dichotomization from Monte-Carlo Simulations -- Part 2: Monte-Carlo Methods in Missing Data -- 7. Hybrid Monte-Carlo in Multiple Missing Data Imputations with Application to a Bone Fracture Data -- 8.
Methods for Handling Incomplete Longitudinal Data due to Missing at Random Dropout -- 9. Applications of Simulation for Missing Data Issues in Longitudinal Clinical Trials -- 10. Application of Markov Chain Monte Carlo Multiple
Imputation Method to Deal with Missing Data From the Mechanism of MNAR in Sensitivity Analysis for a Longitudinal Clinical Trial -- 11. Fully Bayesian Methods for Missing Data under Ignitability Assumption -- Part 3: Monte-Carlo in
Statistical Modellings -- 12. Markov-Chain Monte-Carlo Methods in Statistical modelling -- 13. Monte-Carlo Simulation in Modeling for Hierarchical Linear Mixed Models -- 14. Monte-Carlo Simulation of Correlated Binary Responses -- 15.
Monte Carlo Methods in Financial Modeling -- 16. Bayesian Intensive Computations in Elliptical Models.
ISBN:9789811033070
Series:eBooks
Series:Springer eBooks
Series:Springer 2017 package
Keywords: Statistics , Biostatistics , Statistics , Statistics for Life Sciences, Medicine, Health Sciences , Biostatistics
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Call number:9783319486604:ONLINE Show nearby items on shelf
Title:Applied Physics of External Radiation Exposure Dosimetry and Radiation Protection
Author(s): Rodolphe Antoni
Date:2017
Size:1 online resource (XV, 470 p. 277 illus., 21 illus. in color p.)
Contents:Basic Physical Quantities Used in Radiation Protection for External Exposure -- Interaction of Ionizing Radiation in Tissue : Assessment of Kerma and Absorbed Dose -- Protection and Operational Quantities, Dosimeter Calibration --
Assessment of External Exposure Sources -- Principles of Protection against External Radiation Exposure -- Monte Carlo Method Applied to Dosimetry and Radiation Protection
ISBN:9783319486604
Series:eBooks
Series:Springer eBooks
Series:Springer 2017 package
Keywords: Physics , Radiology , Particle acceleration , Medical physics , Radiation , Biomedical engineering , Physics , Medical and Radiation Physics , Diagnostic Radiology , Biomedical Engineering , Particle Acceleration and Detection, Beam Physics , Numerical and Computational Physics, Simulation
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Call number:9783319434766:ONLINE Show nearby items on shelf
Title:Discrete Probability Models and Methods Probability on Graphs and Trees, Markov Chains and Random Fields, Entropy and Coding
Author(s): Pierre Brémaud
Date:2017
Size:1 online resource (XIV, 559 p. 92 illus p.)
Contents:Introduction -- 1.Events and probability -- 2.Random variables -- 3.Bounds and inequalities -- 4.Almost-sure convergence -- 5.Coupling and the variation distance -- 6.The probabilistic method -- 7.Codes and trees -- 8.Markov chains --
9.Branching trees -- 10.Markov fields on graphs -- 11.Random graphs -- 12.Recurrence of Markov chains -- 13.Random walks on graphs -- 14.Asymptotic behaviour of Markov chains -- 15.Monte Carlo sampling -- 16. Convergence rates --
Appendix -- Bibliography
ISBN:9783319434766
Series:eBooks
Series:Springer eBooks
Series:Springer 2017 package
Keywords: Mathematics , Computer communication systems , Coding theory , Mathematical statistics , Probabilities , Graph theory , Mathematics , Probability Theory and Stochastic Processes , Probability and Statistics in Computer Science , Graph Theory , Coding and Information Theory , Computer Communication Networks
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Call number:9781420079425:ONLINE Show nearby items on shelf
Title:Handbook of Markov Chain Monte Carlo [electronic resource]
Author(s): Steve Brooks (ed.)
Andrew Gelman (ed.)
Date:2011
Edition:1st ed.
Publisher:Taylor & Francis Group
Size:1 electronic resource (619 p)
Contents:Introduction to Markov Chain Monte Carlo -- A short history of MCMC: subjective recollections from incomplete data -- Reversible jump MCMC -- Optimal proposal distributions and adaptive MCMC -- MCMC using Hamiltonian Dynamics -- Inference from simul ations and monitoring convergence -- Implementing MCMC: estimating with confidence -- Perfection within reach: exact MCMC sampling -- Spatial point processes -- The data augmentation algorithm: theory and methodology -- Importance sampling, simulated temp ering, and umbrella sampling -- Likelihood-free MCMC -- MCMC in the analysis of genetic data on related individuals -- An MCMC=based analysis of a mulitlevel model for functional MRI data -- Partially collapsed Gibbs sampling and path-adaptive metropolis- hastings in high-energy astrophysics -- Posterior exploration for computationally intensive forward models -- Statistical ecology -- Gaussian random field models for spatial data -- Modeling preference changes via a Hidden Markovltem response theory model -- Parallel Bayesian MCMC imputation for multiple distributed lag models: a case study in environmental epidemiology -- MCMC for state-space models -- MCMC in educational research -- Applications of MCMC in fisheries science -- Model comparison and simul ation for hierarchical models: analyzing rural-urban migration in Thailand.
ISBN:9781420079425
Keywords: Markov processes , Monte Carlo method
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Call number:1118632168:ONLINE Show nearby items on shelf
Title:Simulation and the Monte Carlo Method, Third Edition
Author(s): Rubinstein
Date:2016
Publisher:Wiley
Size:1 online resource (433 p.)
ISBN:9781118632161
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0470258799:ONLINE Show nearby items on shelf
Title:Student Solutions Manual to Accompany Simulation and the Monte Carlo Method, Second Edition
Author(s): Kroese
Date:2007
Publisher:Wiley-Interscience
Size:1 online resource (189 p.)
ISBN:9780470258798
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0470177942:ONLINE Show nearby items on shelf
Title:Simulation and the Monte Carlo Method, Second Edition
Author(s): Rubinstein
Date:2007
Publisher:Wiley-Interscience
Size:1 online resource (373 p.)
ISBN:9780470177945
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:SPRINGER-2016-9783319335070:ONLINE Show nearby items on shelf
Title:Monte Carlo and Quasi-Monte Carlo Methods MCQMC, Leuven, Belgium, April 2014
Author(s):
Date:2016
Size:1 online resource (57 p.)
Note:10.1007/978-3-319-33507-0
Contents:Part I Invited papers -- Multilevel Monte Carlo Implementation for SDEs driven by Truncated Stable Processes -- Construction of a Mean Square Error Adaptive Euler–Maruyama Method With Applications in Multilevel Monte Carlo -- Vandermonde Nets and Vandermonde Sequences -- Path Space Markov Chain Monte Carlo Methods in Computer Graphics -- Walsh Figure of Merit for Digital Nets: An Easy Measure for Higher Order Convergent QMC -- Some Results on the Complexity of Numerical Integration -- Approximate Bayesian Computation: A Survey on Recent Results -- Part II Contributed papers -- Multilevel Monte Carlo Simulation of Statistical Solutions to the Navier–Stokes Equations -- Unbiased Simulation of Distributions with Explicitly Known Integral Transforms -- Central Limit Theorem for Adaptive Multilevel Splitting Estimators in an Idealized Setting -- Comparison between LS-Sequences and β -adic van der Corput Sequences -- Computational Higher Order Quasi-Monte Carlo Integration -- Numerical
Computation of Multivariate Normal Probabilities using Bivariate Conditioning -- Non-nested Adaptive Timesteps in Multilevel Monte Carlo Computations -- On ANOVA Decompositions of Kernels and Gaussian Random Field Paths -- The Mean Square Quasi-Mont e Carlo Error for Digitally Shifted Digital Nets -- Uncertainty and Robustness in Weather Derivative Models -- Reliable Adaptive Cubature Using Digital Sequences -- Optimal Point Sets for Quasi-Monte Carlo Integration of Bivariate Periodic Functions with Bounded Mixed Derivatives -- Adaptive Multidimensional Integration Based on Rank-1 Lattices -- Path Space Filtering -- Tractability of Multivariate Integration in Hybrid Function Spaces -- Derivative-based Global Sensitivity Measures and Their Link with S obol’ Sensitivity Indices -- Bernstein Numbers and Lower Bounds for the Monte Carlo Error -- A Note on the Importance of Weak Convergence Rates for SPDE Approximations in Multilevel Monte Carlo Schemes -- A Strategy for Parallel
Implementations of Stochastic Lagrangian Simulation -- A New Rejection Sampling Method for Truncated Multivariate Gaussian Random Variables Restricted to Convex Sets -- Van der Corput and Golden Ratio Sequences Along the Hilbert Space-Filling Curve -- Uniform Weak Tractability of Weighted Integration -- Incremental Greedy Algorithm and Its Applications in Numerical Integration -- On “Upper Error Bounds for Quadrature Formulas on Function Classes” by K K Frolov -- Tractability of Function Approxi mation With Product Kernels -- Discrepancy Estimates for Acceptance-Rejection Samplers Using Stratified Inputs -- List of Participants -- Index
ISBN:9783319335070
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Springer Proceedings in Mathematics & Statistics: 163
Keywords: Mathematics , Applied mathematics , Engineering mathematics , Computer mathematics , Mathematics , Computational Mathematics and Numerical Analysis , Applications of Mathematics
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Call number:SPRINGER-2016-9783319316116:ONLINE Show nearby items on shelf
Title:Probability for Physicists
Author(s): Simon Sirca
Date:2016
Size:1 online resource (29 p.)
Note:10.1007/978-3-319-31611-6
Contents:Basic Terminology -- Probability Distributions -- Special Continuous Probability Distributions -- Expected Values -- Special Discrete Probability Distributions -- Convolution -- Samples -- Estimation of Parameters and Statistical
Tests -- Regression -- Entropy -- Markov Processes -- Generation of Pseudorandom Numbers -- Monte Carlo Method -- Stochastic Population Modeling
ISBN:9783319316116
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Physics , Chemistry, Physical and theoretical , Mathematical physics , Probabilities , Statistical physics , Dynamical systems , Physics , Statistical Physics, Dynamical Systems and Complexity , Mathematical Methods in Physics , Probability Theory and Stochastic Processes , Mathematical Applications in the Physical Sciences , Theoretical and Computational Chemistry
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Call number:SPRINGER-2016-9783319272658:ONLINE Show nearby items on shelf
Title:Basic Concepts in Computational Physics
Author(s): Benjamin A Stickler
Date:2016
Edition:2nd ed. 2016
Size:1 online resource (409 p.)
Note:10.1007/978-3-319-27265-8
Contents:Some Basic Remarks -- Part I Deterministic Methods -- Numerical Differentiation -- Numerical Integration -- The KEPLER Problem -- Ordinary Differential Equations – Initial Value Problems -- The Double Pendulum -- Molecular Dynamics --
Numerics of Ordinary Differential Equations - Boundary Value Problems -- The One-Dimensional Stationary Heat Equation -- The One-Dimensional Stationary SCHRÖDINGER Equation -- Partial Differential Equations -- Part II Stochastic
Methods -- Pseudo Random Number Generators -- Random Sampling Methods -- A Brief Introduction to Monte-Carlo Methods -- The ISING Model -- Some Basics of Stochastic Processes -- The Random Walk and Diffusion Theory -- MARKOV-Chain
Monte Carlo and the POTTS Model -- Data Analysis -- Stochastic Optimization -- Appendix: The Two-Body Problem -- Solving Non-Linear Equations. The NEWTON Method -- Numerical Solution of Systems of Equations -- Fast Fourier Transform --
Basics of Probability Theory -- Phase Transitions -- Fractional Integrals and Derivatives in 1D -- Least Squares Fit -- Deterministic Optimization
ISBN:9783319272658
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Physics , Chemistry, Physical and theoretical , Computer mathematics , Applied mathematics , Engineering mathematics , Physics , Numerical and Computational Physics , Appl.Mathematics/Computational Methods of Engineering , Computational Mathematics and Numerical Analysis , Theoretical and Computational Chemistry
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Call number:SPRINGER-2016-9783319255897:ONLINE Show nearby items on shelf
Title:Stochastic Analysis for Finance with Simulations
Author(s): Geon Ho Choe
Date:2016
Size:1 online resource (107 p.)
Note:10.1007/978-3-319-25589-7
Contents:Preface -- Acknowledgements -- List of Figures -- List of Tables -- List of Simulations -- Fundamental Concepts -- Financial Derivatives -- The Lebesgue Integral -- Basic Probability Theory -- Conditional Expectation -- Stochastic Processes -- Brown ian Motion -- Girsanov's Theorem -- The Reflection Principle of Brownian Motion -- The Ito Integral -- The Ito Formula -- Stochastic Differential Equations -- The Feynmann-Kac Theorem -- The Binomial Tree Method for Option Pricing -- The Black-Scholes-Mer ton Differential Equation -- The Martingale Method -- Pricing of Vanilla Options -- Pricing of Exotic Options -- American Options -- The Capital Asset Pricing Model -- Dynamic Programming -- Bond Pricing -- Interest Rate Models -- Numeraires -- Numerical Estimation of Volatility -- Time Series -- Random Numbers -- The Monte Carlo Method for Option Pricing -- Numerical Solution of the Black-Scholes-Merton Equation -- Numerical Solution of Stochastic Differential Equations. Appendices --
Solutions for Selected Problems -- Glossary -- References -- Index.
ISBN:9783319255897
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Mathematics , Economics, Mathematical , Mathematics , Mathematics, general , Quantitative Finance
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Call number:SPRINGER-2014-9784431545170:ONLINE Show nearby items on shelf
Title:Geometrically Constructed Markov Chain Monte Carlo Study of Quantum Spin-phonon Complex Systems [electronic resource]
Author(s): Hidemaro Suwa
Date:2014
Publisher:Tokyo : Springer Japan : Imprint: Springer
Size:1 online resource
Note:In this thesis, novel Monte Carlo methods for precisely calculating the critical phenomena of the effectively frustrated quantum spin system are developed and applied to the critical phenomena of the spin-Peierls systems. Threesignificant methods are introduced for the first time: a new optimization algorithm of the Markov chain transition kernel based on the geometric weight-allocation approach, the extension of the worm (directed-loop) algorithm tononconserved particles, and the combination with th e level spectroscopy. Utilizing these methods, the phase diagram of the one-dimensional XXZ spin-Peierls system is elucidated. Furthermore, the multi-chain and two-dimensionalspin-Peierls systems with interchain lattice interaction are investigated. The unbiased simulation shows that the interesting quantum phase transition between the 1D-like liquid phase and the macroscopically-degenerated dimer phaseoccurs on the fully-frustrated parameter line that separates the doubly-degenerated dimer phases in the two-dimensional phase diagram. The spin-phonon interaction in the spin-Peierls system introduces the spin frustration, whichusually hinders the quantum Monte Carlo analysis, owing to the notorious negative sign problem.In this thesis, the author has succ eeded in precisely calculating the critical phenomena of the effectively frustrated quantum spin systemby means of the quantum Monte Carlo method without the negative sign
Contents:Introduction
Geometric Allocation Approach in Markov Chain Monte Carlo
Monte Carlo Method for Spin
Peierls Systems
Quantum Monte Carlo Level Spectroscopy
XXZ Spin
Peierls Chain
Multi
chain Spin
Peierls Systems
Summary
ISBN:9784431545170
Series:eBooks
Series:SpringerLink
Series:Springer Theses, Recognizing Outstanding Ph.D. Research, 2190-5053
Series:Physics and Astronomy (Springer-11651)
Keywords: Computer simulation , Quantum theory , Engineering mathematics
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Call number:SPRINGER-2014-9783319037622:ONLINE Show nearby items on shelf
Title:Data Analysis [electronic resource] : Statistical and Computational Methods for Scientists and Engineers
Author(s): Siegmund Brandt
Date:2014
Edition:4th ed. 2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory andpractical problems. The co ncise mathematical treatment of the subject matter is illustrated by many examples, and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysisand graphical representation as well as many exam ple programs and solutions to programming problems. The programs (source code, Java classes, and documentation) and extensive appendices to the main text are available for free downloadfrom the books page at www.springer.com. Contents Probabilities. Rando m variables. Random numbers and the Monte Carlo Method. Statistical distributions (binomial, Gauss, Poisson). Samples. Statistical tests. Maximum Likelihood.Least Squares. Regression. Minimization. Analysis of Variance. Time series analysis. Audience The book is conceived both as an introduction and as a work of reference. In particular it addresses itself to students, scientists andpractitioners in science and engineering as a help in the analysis of their data in laboratory courses, working for bachelor or master degrees, in thesis work, and in research and professional work. The book is concise, but gives asufficiently rigorous mathematical treatment of practical statistical methods for data analysis it can be of great use to all who are involved with data analysis. Physicalia This lively and erudite treatise covers the theory ofthe main statistical tools and their practical applicationsa first rate university textbook, and good background material for the practicing physicist. Physics Bulletin The Aut hor Siegmund Brandt is Emeritus Professor of Physicsat the University of Siegen. With his group he worked on experiments in elementary-particle physics at the research centers DESY in
Contents:Introduction
Probabilities
Random Variables: Distributions
Computer
Generated Random Numbers: The Monte Carlo Method
Some Important Distributions and Theorems
Samples
The Method of Maximum Likelihood
Testing Statistical Hypotheses
The Method of Least Squares
Function Minimization
Analysis of Variance
Linear and Polynomial Regression
Time
Series Analysis
A) Matrix Calculations
B) Combinatorics
C) Formulas and Methods for the Computation of Statistical Functions
D) The Gamma Function and Related Functions: Methods and Programs for their Computation
ISBN:9783319037622
Series:eBooks
Series:SpringerLink
Series:Physics and Astronomy (Springer-11651)
Keywords: Chemistry Mathematics , Mathematical physics , Engineering mathematics
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Call number:SPRINGER-2014-9783319013008:ONLINE Show nearby items on shelf
Title:Current Challenges in Stability Issues for Numerical Differential Equations [electronic resource] : Cetraro, Italy 2011, Editors: Luca Dieci, Nicola Guglielmi
Author(s): Wolf-Jrgen Beyn
Luca Dieci
Nicola Guglielmi
Ernst Hairer
Jess Mara Sanz-Serna
Marino Zennaro
Date:2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:This volume addresses some of the research areas in the general field of stability studies for differential equations, with emphasis on issues of concern for numerical studies. Topics considered include: (i) the long timeintegration of Hamiltonian Or dinary DEs and highly oscillatory systems, (ii) connection between stochastic DEs and geometric integration using the Markov chain Monte Carlo method, (iii) computation of dynamic patterns in evolutionarypartial DEs, (iv) decomposition of matrices dependi ng on parameters and localization of singularities, and (v) uniform stability analysis for time dependent linear initial value problems of ODEs. The problems considered in this volumeare of interest to people working on numerical as well as qualitative as pects of differential equations, and it will serve both as a reference and as an entry point into further research
Contents:Studies on current challenges in stability issues for numerical differential equations
Long
Term Stability of Symmetric Partitioned Linear Multistep Methods
Markov Chain Monte Carlo and Numerical Differential Equations
Stability and Computation of Dynamic Patterns in PDEs
Continuous Decompositions and Coalescing Eigen values for Matrices Depending on Parameters
Stability of linear problems: joint spectral radius of sets of matrices
ISBN:9783319013008
Series:eBooks
Series:SpringerLink
Series:Lecture Notes in Mathematics, 0075-8434 : v2082
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Matrix theory , Differential Equations , Differential equations, partial , Computer science Mathematics , Algorithms
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Call number:SPRINGER-2014-9783319011776:ONLINE Show nearby items on shelf
Title:Background Processes in the Electrostatic Spectrometers of the KATRIN Experiment [electronic resource]
Author(s): Susanne Mertens
Date:2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:Neutrinos continue tobe the most mysterious and, arguably, the most fascinating particles of the Standard Model as their intrinsic properties such as absolute mass scale and CP properties are unknown. The open question of theabsolute neutrino mass sc ale will be addressed with unprecedented accuracy by the Karlsruhe Tritium Neutrino (KATRIN) experiment, currently under construction. This thesisfocusses on the spectrometer part of KATRIN and backgroundprocesses therein. Various background sources such as small Penning traps, as well as nuclear decays from single radon atoms are fully characterized here for the first time. Most importantly, however, it was possible to reduce thebackground in the spectrometer by more than five orders of magnitude by elim inating Penning traps and by developing a completely new background reduction method by stochastically heating trapped electrons using electron cyclotronresonance (ECR). The workbeautifully demonstrates that the obstacles and challenges in measuring the a bsolute mass scale of neutrinos can be met successfully if novel experimental tools (ECR) and novel computing methods(KASSIOPEIA) are combined to allow almost background-freetritium -spectroscopy
Contents:Abstract
Introduction and objectives of the thesis
Neutrino Physics
The KATRIN experiment
Monte Carlo simulation package
Muon induced background
Background due to Penning traps
Background due to stored electrons following nuclear decays
Background due to stored electrons following nuclear decays
Conclusion
Optimization of the spectrometer transmission properties with the air coil system
Comparison of transmission measurements at the pre
spectrometer with Kassiopeia simulations
Alternative methods of removing stored electrons
ISBN:9783319011776
Series:eBooks
Series:SpringerLink
Series:Springer Theses, Recognizing Outstanding Ph.D. Research, 2190-5053
Series:Physics and Astronomy (Springer-11651)
Keywords: Particle acceleration
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Call number:SPRINGER-2014-9783319007267:ONLINE Show nearby items on shelf
Title:Time-Dependent CP Violation Measurements [electronic resource] : Analyses of Neutral B Meson to Double-Charm Decays at the Japanese Belle Experiment
Author(s): Markus Rhrken
Date:2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:This thesis describes a high-quality, high-precision method for the data analysis of an interesting elementary particle reaction. The data was collected at the Japanese B-meson factory KEKB with the Belle detector, one of the mostsuccessful large-sca le experiments worldwide. CP violation is a subtle quantum effect that makes the world look different when simultaneously left and right and matter and antimatter are exchanged. This being a prerequisitefor ourown world to havedeveloped from the big bang, there are only a few experimental indications of such effects, and their detectionrequiresvery intricatetechniques. The discovery of CP violation in B meson decays garneredKobayashi and Maskawa, who had predicted these findings as early as 1973, the 2008 Nobel prize in physics.This thesis describes in great detailwhat are by far the best measurements of branching ratios and CP violation parameters intwo special reactions with two charm mesons in the final state. It presents an in-depth but accessible ove rview of the theory, phenomenology, experimental setup, data collection, Monte Carlo simulations, (blind) statistical dataanalysis, and systematic uncertainty studies
Contents:Theoretical Foundations
The Belle Experiment
Analysis Methods
Reconstruction and Selection
Branching Fraction Measurements
Time
Dependent Measurements
ISBN:9783319007267
Series:eBooks
Series:SpringerLink
Series:Springer Theses, Recognizing Outstanding Ph.D. Research, 2190-5053
Series:Physics and Astronomy (Springer-11651)
Keywords: Quantum theory
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Call number:SPRINGER-2013-9789400758391:ONLINE Show nearby items on shelf
Title:Statistical Physics of Nanoparticles in the Gas Phase [electronic resource]
Author(s): Klavs Hansen
Date:2013
Publisher:Dordrecht : Springer Netherlands : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Thermal processes are ubiquitous and an understanding of thermal phenomena is essential for a complete description of the physics of nanoparticles, both for the purpose of modeling the dynamics of the particles and for the correctinterpretation of ex perimental data. This book has the twofold aim to present coherently the relevant results coming from the recent scientific literature and to guide the readers through the process of deriving results, enabling themto explore the limits of the mathematical approximations and test the power of the method. The book is focused on the fundamental properties of nanosystems in the gas phase. For this reason there is a strong emphasis on microcanonicalphysics. Each chapter is enrichedwith exercises and 3 Appendic es provide additional usefulmaterials
Note:Springer eBooks
Contents:The relation between classical and quantum statistics
Microcanonical temperature
Thermal properties of vibrations
Rate constants for emission of atoms, electrons and photons
The evaporative ensemble
Abundance distributions large scale features
Molecular dynamics and Monte Carlo simulations
Thermal excitation of valence electrons
He droplets
ISBN:9789400758391
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series on Atomic, Optical, and Plasma Physics, 1615-5653 : v73
Series:Physics and Astronomy (Springer-11651)
Keywords: Thermodynamics
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Call number:SPRINGER-2013-9789400748255:ONLINE Show nearby items on shelf
Title:Automatic trend estimation [electronic resource]
Author(s): Calin Vamos
Maria Craciun
Date:2013
Publisher:Dordrecht : Springer Netherlands : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Our book introduces a method to evaluate the accuracy of trend estimation algorithms under conditions similar to those encountered in real time series processing. This method is based on Monte Carlo experiments with artificialtime series numerically generated by an original algorithm. The second part of the book contains several automatic algorithms for trend estimation and time series partitioning. The source codes of the computer programs implementingthese original automatic algorithms are given in the appendix and will be freely available on the web. The book contains clear statement of the conditions and the approximations under which the algorithms work, as well as the properinterpretation of their results. We illustrate the functioning of the a nalyzed algorithms by processing time series from astrophysics, finance, biophysics, and paleoclimatology. The numerical experiment method extensively used in ourbook is already in common use in computational and statistical physics
Note:Springer eBooks
Contents:Discrete stochastic processes and time series
Trend definition
Finite AR(1) stochastic process
Monte Carlo experiments
Monte Carlo statistical ensembles
Numerical generation of trends
Numerical generation of noisy time series
Statistical hypothesis testing
Testing the i.i.d. property
Polynomial fitting
Linear regression
Polynomial fitting
Polynomial fitting of artificial time series
An astrophysical example
Noise smoothing
Moving average
Repeated moving average (RMA)
Smoothing of artificial time series
A financial example
Automatic estim
ISBN:9789400748255
Series:e-books
Series:SpringerLink (Online service)
Series:SpringerBriefs in Physics, 2191-5423
Series:Physics and Astronomy (Springer-11651)
Keywords: Computer simulation , Computer science Mathematics , Distribution (Probability theory)
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Call number:SPRINGER-2013-9783642351068:ONLINE Show nearby items on shelf
Title:Strongly Correlated Systems [electronic resource] : Numerical Methods
Author(s): Adolfo Avella
Ferdinando Mancini
Date:2013
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This volume presents, for the very first time, an exhaustive collection of those modern numerical methods specifically tailored for the analysis of Strongly Correlated Systems. Many novel materials, with functional propertiesemerging from macroscopic quantum behaviors at the frontier of modern research in physics, chemistry and material science, belong to this class of systems. Any technique is presented in great detail by its own inventor or by one of theworld-wide recognized main contributors. The exposition has a clear pedagogical cut and fully reports on the most relevant case study where the specific technique showed to be very successful in describing and enlightening the puzzlingphysics of a particular strongly correlated system. The book is i ntended for advanced graduate students and post-docs in the field as textbook and/or main reference, but also for other researchers in the field who appreciate consultinga single, but comprehensive, source or wishes to get acquainted, in a as painless as possible way, with the working details of a specific technique
Note:Springer eBooks
Contents:1. Ground State and Finite Temperature Lanczos Method
2.The Density Matrix Renormalization Group
3. Matrix Product State Algorithms: DMRG, TEBD and Relatives
4.Quantum Criticality with the Multi
scale Entanglement Renormalization Ansatz
5. The Time
Dependent Density Matrix Renormalization Groupd
6.Loop Algorithm
7. Stochastic Series Expansion Quantum Monte Carlo
8. VariatonalMonte Carlo and Markov Chanis for Computational Physics
9. Coupled Cluster Theories for Strongly Correlated Molecular Systems
10. Diagrammatic Monte Carlo and Worm Algorithm Techniques
ISBN:9783642351068
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Solid-State Sciences, 0171-1873 : v176
Series:Physics and Astronomy (Springer-11651)
Keywords: Mathematical physics
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Call number:SPRINGER-2013-9783319008851:ONLINE Show nearby items on shelf
Title:Uncertainty Quantification in Computational Fluid Dynamics [electronic resource]
Author(s): Hester Bijl
Didier Lucor
Siddhartha Mishra
Christoph Schwab
Date:2013
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Fluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flowuncertainty, given this initial randomness. It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkinmethods and modified versions of the stochastic collocatio n methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space. The methods are also complemented by concrete applications such asflows around aerofoils and rockets, problems of aeroelasticity (fluid-structure int eractions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposedmethod as well as comparisons of different approaches
Note:Springer eBooks
Contents:Timothy Barth: Non
Intrusive Uncertainty Propagation with Error Bounds for Conservation Laws Containing Discontinuities
Philip Beran and Bret Stanford: Uncertainty Quantification in Aeroelasticity
Bruno Desprs, Gal Potte and Didier Lucor: Robust uncertainty propagation in systems of conservation laws with the entropy closure method
Richard P. Dwight, Jeroen A.S. Witteveen and Hester Bijl: Adaptive Uncertainty Quantification for Computational Fluid Dynamics
Chris Lacor, Cristian Dinescu, Charles Hirsch and Sergey Smirnov: Implementation of intrusive Polynomial Chaos in CFD cod
ISBN:9783319008851
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Computational Science and Engineering, 1439-7358 : v92
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer science Mathematics , Computer science , Engineering mathematics , Astronautics
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Call number:SPRINGER-2013-9783319004013:ONLINE Show nearby items on shelf
Title:Computational Physics [electronic resource] : Simulation of Classical and Quantum Systems
Author(s): Philipp O.J Scherer
Date:2013
Edition:2nd ed. 2013
Publisher:Heidelberg : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This textbook presents basic and advanced computational physics in a very didactic style. It contains very-well-presented and simple mathematical descriptions of many of the most important algorithms used in computational physics.Many clear mathemati cal descriptions of important techniques in computational physics are given. The first part of the book discusses the basic numerical methods. A large number of exercises and computer experiments allows to study theproperties of these methods. The second part concentrates on simulation of classical and quantum systems. It uses a rather general concept for the equation of motion which can be applied to ordinary and partial differential equations.Several classes of integration methods are discussed includin g not only the standard Euler and Runge Kutta method but also multistep methods and the class of Verlet methods which is introduced by studying the motion in Liouville space.Besides the classical methods, inverse interpolation is discussed, together with the popular combined methods by Dekker and Brent and a not so well known improvement by Chandrupatla. A general chapter on the numerical treatment ofdifferential equations provides methods of finite differences, finite volumes, finite elements and boundar y elements together with spectral methods and weighted residual based methods. A comparison of several methods for quantumsystems is performed, containing pseudo-spectral methods, finite differences methods, rational approximation to the time evolution op erator, second order differencing and split operator methods. The book gives simple but non trivialexamples from a broad range of physical topics trying to give the reader insight into the numerical treatment but also the simulated problems. Rotational mo tion is treated in much detail to describe the motion of rigid rotors which canbe just a simple spinning top or a collection of molecules or planets. The behaviour of simple quantum systems is studied t
Note:Springer eBooks
Contents:Part I Numerical Methods
Error Analysis
Interpolation
Numerical Differentiation
Numerical Integration
Systems of Inhomogeneous Linear Equations
Roots and Extremal Points
Fourier Transformation
Random Numbers and Monte
Carlo Methods
Eigenvalue Problems
Data Fitting
Discretization of Differential Equations
Equations of Motion
Part II Simulation of Classical and Quantum Systems
Rotational Motion
Molecular Dynamics
Thermodynamic Systems
Random Walk and Brownian Motion
Electrostatics
Waves
Diffusion
Nonlinear Systems
Simple Quantum S
ISBN:9783319004013
Series:e-books
Series:SpringerLink (Online service)
Series:Graduate Texts in Physics, 1868-4513
Series:Physics and Astronomy (Springer-11651)
Keywords: Chemistry , Engineering mathematics
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Call number:SPRINGER-2013-9781461485117:ONLINE Show nearby items on shelf
Title:Finance with Monte Carlo [electronic resource]
Author(s): Ronald W Shonkwiler
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This text introduces upper division undergraduate/beginning graduate students in mathematics, finance, or economics, to the core topics of a beginning course in finance/financial engineering. Particular emphasis is placed onexploiting the power of th e Monte Carlo method to illustrate and explore financial principles. Monte Carlo is the uniquely appropriate tool for modeling the random factors that drive financial markets and simulating their implications.The Monte Carlo method is introduced early and it is used in conjunction with the geometric Brownian motion model (GBM) to illustrate and analyze the topics covered in the remainder of the text. Placing focus on Monte Carlo methodsallows for students to travel a short road from theory to practical ap plications. Coverage includes investment science, mean-variance portfolio theory, option pricing principles, exotic options, option trading strategies, jumpdiffusion and exponential Lvy alternative models, and the Kelly criterion for maximizing investment growth. Novel features: inclusion of both portfolio theory and contingent claim analysis in a single text pricing methodology forexotic options expectation analysis of option trading strategies pricing models that transcend the BlackScholes framework opt imizing investment allocations concepts thoroughly explored through numerous simulation exercises numerousworked examples and illustrations The mathematical background required is a year and one-half course in calculus, matrix algebra covering solutions o f linear systems, and a knowledge of probability including expectation, densities andthe normal distribution. A refresher for these topics is presented in the Appendices. The programming background needed is how to code branching, loops and subroutines in some mathematical or general purpose language. The mathematicalbackground required is a year and one-half course in calculus, matrix algebra covering solutions of linear systems, and a knowledge o
Note:Springer eBooks
Contents:1. Geometric Brownian Motion and the Efficient Market Hypothesis
2. Return and Risk
3. Forward and Option Contracts and their Pricing
4. Pricing Exotic Options
5. Option Trading Strategies
6. Alternative to GBM Prices
7. Kelly's Criterion
Appendices
A. Some Mathematical Background Topics
B. Stochastic Calculus
C. Convergence of the Binomial Method
D. Variance Reduction Techniques
E. Shell Sort
F. Next Day Prices Program
References
List of Notation
List of Algorithms
Index
ISBN:9781461485117
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Undergraduate Texts in Mathematics and Technology, 1867-5506
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Finance , Numerical analysis , Distribution (Probability theory)
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Call number:SPRINGER-2013-9781461479840:ONLINE Show nearby items on shelf
Title:Statistics and Analysis of Scientific Data [electronic resource]
Author(s): Massimiliano Bonamente
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Statistics and Analysis of Scientific Data covers the foundations of probability theory and statistics, and a number of numerical and analytical methods that are essential for the present-day analyst of scientific data. Topicscovered include probabil ity theory, distribution functions of statistics, fits to two-dimensional datasheets and parameter estimation, Monte Carlo methods and Markov chains. Equal attention is paid to the theory and its practicalapplication, and results from classic experiments in various fields are used to illustrate the importance of statistics in the analysis of scientific data. The main pedagogical method is a theory-then-application approach, whereemphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and proactive use of the material for practical applications. The level is appropriate for undergraduatesand beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required.The book includes manynumerical tables of data, as well as exercises and examples to aid the students' understanding of the topic
Note:Springer eBooks
Contents:Theory of Probability
Random Variables and Their Distribution
Sum and Functions of Random Variables
Estimate of Mean and Variance and Confidence Intervals
Distribution Function of Statistics and Hypothesis Testing
Maximum Likelihood Fit to a Two
Variable Dataset
Goodness of Fit and Parameter Uncertainty
Comparison Between Models
Monte Carlo Methods
Markov Chains and Monte Carlo Markov Chains
A: Numerical Tables
B: Solutions
ISBN:9781461479840
Series:e-books
Series:SpringerLink (Online service)
Series:Graduate Texts in Physics, 1868-4513
Series:Physics and Astronomy (Springer-11651)
Keywords: Distribution (Probability theory) , Mathematical statistics
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Call number:SPRINGER-2012-9783642294884:ONLINE Show nearby items on shelf
Title:An Introduction to Kinetic Monte Carlo Simulations of Surface Reactions [electronic resource]
Author(s): A.P.J Jansen
Date:2012
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Kinetic Monte Carlo (kMC) simulations still represent a quite new area of research, with a rapidly growing number of publications. Broadly speaking, kMC can be applied to any system describable as a set of minima of apotential-energy surface, the evo lution of which will then be regarded as hops from one minimum to a neighboring one. The hops in kMC are modeled as stochastic processes and the algorithms use random numbers to determine at which timesthe hops occur and to which neighboring minimum they go. Sometimes this approach is also called dynamic MC or Stochastic Simulation Algorithm, in particular when it is applied to solving macroscopic rate equations. This bookhas two objectives. First, it is a primer on the kMC method (predominantly using t he lattice-gas model) and thus much of the book will also be useful for applications other than to surface reactions. Second, it is intended to teach thereader what can be learned from kMC simulations of surface reaction kinetics. With these goals in min d, the present text is conceived as a self-contained introduction for students and non-specialist researchers alike who areinterested in entering the field and learning about the topic from scratch
Note:Springer eBooks
Contents:Introduction
Stochastic Model for the Description of Surface Reaction Systems
Kinetic Monte Carlo Algorithms
How to Get Kinetic Parameters
Modeling Surface Reactions I
Modeling Surface Reactions II
Examples
New Developments
Glossary
Index
ISBN:9783642294884
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Physics, 0075-8450 : v856
Series:Physics and Astronomy (Springer-11651)
Keywords: Chemistry , Surfaces (Physics)
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Call number:SPRINGER-2012-9783642272257:ONLINE Show nearby items on shelf
Title:Bayesian Methods in Structural Bioinformatics [electronic resource]
Author(s): Thomas Hamelryck
Kanti Mardia
Jesper Ferkinghoff-Borg
Date:2012
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book is an edited volume, the goal of which is to provide an overview of the current state-of-the-art in statistical methods applied to problems in structural bioinformatics (and in particular protein structure prediction,simulation, experimenta l structure determination and analysis). It focuses on statistical methods that have a clear interpretation in the framework of statistical physics, rather than ad hoc, black box methods based on neural networksor support vector machines. In addition, the emphasis is on methods that deal with biomolecular structure in atomic detail. The book is highly accessible, and only assumes background knowledge on protein structure, with a minimum ofmathematical knowledge. Therefore, the book includes introductory c hapters that contain a solid introduction to key topics such as Bayesian statistics and concepts in machine learning and statistical physics
Note:Springer eBooks
Contents:Part I Foundations: An Overview of Bayesian Inference and Graphical Models
Monte Carlo Methods for Inferences in High
dimensional Systems
Part II Energy Functions for Protein Structure Prediction: On the Physical Relevance and Statistical Interpretation of Knowledge based Potentials
Statistical Machine Learning of Protein Energetics from Experimentally Observed Structures
A Statistical View on the Reference Ratio Method
Part III Directional Statistics and Shape Theory: Statistical Modelling and Simulation Using the Fisher
Bingham Distribution
Statistics of Bivariate von Mises
ISBN:9783642272257
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Medicine , Bioinformatics
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Call number:SPRINGER-2012-9781461437192:ONLINE Show nearby items on shelf
Title:Markov Bases in Algebraic Statistics [electronic resource]
Author(s): Satoshi Aoki
Hisayuki Hara
Akimichi Takemura
Date:2012
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Algebraic statistics is a rapidly developing field, where ideas from statistics and algebra meet and stimulate new research directions. One of the origins of algebraic statistics is the work by Diaconis and Sturmfels in 1998 onthe use ofGrbner bases for constructing a connected Markov chain for performing conditional tests of a discrete exponential family. In this book we take up this topic and present a detailed summary of developments following theseminal work of Diaconis and Sturmfels. This book i s intended for statisticians with minimal backgrounds in algebra.As we ourselves learned algebraic notions through working on statistical problems and collaborating with notablealgebraists, we hope that this book with many practical statistical problems i s useful for statisticians to start working on the field. Satoshi Aoki obtained his doctoral degree from University of Tokyo in 2004 and is currently anassociate professor in Graduate school of Science and Engineering, Kagoshima University. Hisayuki Hara obtained his doctoral degree from University of Tokyo in 1999 and is currently an associate professor in Faculty of Economics,Niigata University. Akimichi Takemura obtained his doctoral degree from Stanford University in 1982 and is currently a professor in Graduate School of Information Science and Technology, University of Tokyo
Note:Springer eBooks
Contents:Exact tests for contingency tables and discrete exponential families
Markov chain Monte Carlo methods over discrete sample space
Toric ideals and their Grbner bases
Definition of Markov bases and other bases
Structure of minimal Markov bases
Method of distance reduction
Symmetry of Markov bases
Decomposable models of contingency tables
Markov basis for no
three
factor interaction models and some other hierarchical models
Two
way tables with structural zeros and fixed subtable sums
Regular factorial designs with discrete response variables
Group
wise selection
ISBN:9781461437192
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397 : v199
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Algebra , Mathematics , Mathematical statistics
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Call number:SPRINGER-2011-9783790826289:ONLINE Show nearby items on shelf
Title:Advances in Directional and Linear Statistics [electronic resource] : A Festschrift for Sreenivasa Rao Jammalamadaka
Author(s): Martin T Wells
Ashis SenGupta
Date:2011
Publisher:Heidelberg : Physica-Verlag HD
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The present volume consists of papers written by students, colleagues and collaborators of Sreenivasa Rao Jammalamadaka from various countries, and covers a variety of research topics which he enjoys and contributed immensely to
Note:Springer eBooks
Contents:Models for Axial Data
Asymptotic Behavior of the Universally Consistent Conditional U
Statistics for Nonstationary and Absolutely Regular Processes
Regression Models with STARMA Errors An Application to the Study of Temperature Variations in the Antarctic Peninsula
The Generalized von Mises
Fisher Distribution
A New Nonparametric Test of Symmetry
A Semiparametric Bayesian Method of Clustering Genes Using Time
Series of Expression Profiles
On Implementation of the Markov Chain Monte Carlo Stochastic Approximation Algorithm
Stochastic Comparisons of Spacings from Heterog
ISBN:9783790826289
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics
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Call number:SPRINGER-2011-9781441998422:ONLINE Show nearby items on shelf
Title:Modern Issues and Methods in Biostatistics [electronic resource]
Author(s): Mark Chang
Date:2011
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simpleapplication of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data)have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2)high-level complexity of data because they are longitudinal, incomplete, o r latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reductionimpossible, or because of extremely small or large size and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face. This book is written forresearchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce moder n methods in biostatistics and help researchers and students quickly grasp key concepts and methods.Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed inthis s ingle volume
Note:Springer eBooks
Contents:Multiple
Hypothesis Testing Strategy
Pharmaceutical Decision and Game Theory
Noninferiority Trial Design
Adaptive Trial Design
Missing Data Imputation and Analysis
Multivariate and Multistage Survival Data Modeling
Meta
analysis
Data Mining and Signal Detection
Monte Carlo Simulation
Bayesian Methods and Applications
ISBN:9781441998422
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data mining , Mathematics , Engineering
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Call number:SPRINGER-2011-9780817682385:ONLINE Show nearby items on shelf
Title:Integral Methods in Science and Engineering [electronic resource] : Computational and Analytic Aspects
Author(s): Christian Constanda
Paul J Harris
Date:2011
Edition:1
Publisher:Boston : Birkhuser Boston
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The systematic study ofthe physical worldis largely based on the design of mathematical models using many different types of ordinary differential, partial differential, integral, and integro-differential equations. Thesolutions of these equations ar etherefore of great interest to practitioners and to science in general.Witha wealthof cutting-edgeresearch in the field,Integral Methods in Science and Engineering:Computational andAnalytic Aspectsprovides a vivid picture of both the development of theor etical integral techniques and their use in specific science and engineering problems. The volumeis an outgrowth of talks presented by world-renownedresearchers at the Eleventh International Conference on Integral Methods in Science and Engineering held i n Brighton, UK, July 1214, 2010. Thearray of topics they addressis immense,ranging from theoretical advances in boundaryintegral methods to applications of analytic and numerical quadrature techniques as diverse as integral equations, finite and boundary elements, conservation laws, hybrid approaches, and more. With ample coverage of theory andapplications, this bookwill be a valuable resource for researchers in applied mathematics, physics, and mechanical and electrical engineering, forgraduate students in these disciplines, and for various other professionals who useintegration as an essential technique in their work
Note:Springer eBooks
Contents:Preface
Collocation Method for Cauchy Integral Equations in L^2
On a New Definition of the Reynolds Number from the Interplay of Macroscopic and Microscopic Phenomenology
A Self
Consistent Monte Carlo Validation Procedure for Hadron Cancer Therapy Simulation
A General Analytical Solution of the AdvectionDiffusion Equation for Fickian Closure
A Novel Method for Simulating Spectral Nuclear Reactor Criticality by Spatially Dependent Volume Size Control
Adaptive Particle Filter for Stable Distribution
On the Analytical Solution of the Multi
Group Neutron Kinetic Diffusion E
ISBN:9780817682385
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Integral equations , Differential Equations , Differential equations, partial , Computer science Mathematics , Engineering mathematics , Materials
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Call number:SPRINGER-2010-9783642031632:ONLINE Show nearby items on shelf
Title:Monte Carlo Simulation in Statistical Physics [electronic resource] : An Introduction
Author(s): Kurt Binder
Dieter W Heermann
Date:2010
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
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Note:Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations,etc.). Using random num bers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to severalvariants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlomethods. Furthermore a new chapter on the sampling of free-energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups(http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was awarded the Berni J. Alder CECAM Award for Computational Physics 2001 as well as the Boltzmann Medal in 2007
Note:Springer eBooks
Contents:Introduction: Purpose and Scope of This Volume, and Some General Comments
Theoretical Foundation of the Monte Carlo Method and Its Application in Statistical Physics
Guide to Practical Work with the Monte Carlo Method
Some Important Recent Developments of the Monte Carlo Methodology
Quantum Monte Carlo Simulations: An Introduction
Monte Carlo Methods for the Sampling of Free Energy Landscapes
ISBN:9783642031632
Series:e-books
Series:SpringerLink (Online service)
Series:Graduate Texts in Physics, 1868-4513 : v0
Series:Physics and Astronomy (Springer-11651)
Keywords: Chemistry, Physical organic , Mathematical physics , Thermodynamics
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Call number:SPRINGER-2010-9781441959454:ONLINE Show nearby items on shelf
Title:Numerical Analysis for Statisticians [electronic resource]
Author(s): Kenneth Lange
Date:2010
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Every advance in computer architecture and software tempts statisticians to tackle numerically harder problems. To do so intelligently requires a good working knowledge of numerical analysis. This book equips students to crafttheir own software and t o understand the advantages and disadvantages of different numerical methods. Issues of numerical stability, accurate approximation, computational complexity, and mathematical modeling share the limelight in abroad yet rigorous overview of those parts of numerical analysis most relevant to statisticians. In this second edition, the material on optimization has been completely rewritten. There is now an entire chapter on the MM algorithm inaddition to more comprehensive treatments of constrained optimizati on, penalty and barrier methods, and model selection via the lasso. There is also new material on the Cholesky decomposition, Gram-Schmidt orthogonalization, the QRdecomposition, the singular value decomposition, and reproducing kernel Hilbert spaces. The discussions of the bootstrap, permutation testing, independent Monte Carlo, and hidden Markov chains are updated, and a new chapter on advancedMCMC topics introduces students to Markov random fields, reversible jump MCMC, and convergence analysis in Gibb s sampling. Numerical Analysis for Statisticians can serve as a graduate text for a course surveying computationalstatistics. With a careful selection of topics and appropriate supplementation, it can be used at the undergraduate level. It contains enough material for a graduate course on optimization theory. Because many chapters are nearlyself-contained, professional statisticians will also find the book useful as a reference. Kenneth Lange is the Rosenfeld Professor of Computational Genetics in the Dep artments of Biomathematics and Human Genetics and the Chair of theDepartment of Human Genetics, all in the UCLA School of Medicine. His research interests include human genetics, population modeling, bi
Note:Springer eBooks
Contents:Recurrence Relations
Power Series Expansions
Continued Fraction Expansions
Asymptotic Expansions
Solution of Nonlinear Equations
Vector and Matrix Norms
Linear Regression and Matrix Inversion
Eigenvalues and Eigenvectors
Singular Value Decomposition
Splines
Optimization Theory
The MM Algorithm
The EM Algorithm
Newtons Method and Scoring
Local and Global Convergence
Advanced Optimization Topics
Concrete Hilbert Spaces
Quadrature Methods
The Fourier Transform
The Finite Fourier Transform
Wavelets
Generating Random Deviates
Inde
ISBN:9781441959454
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics and Computing, 1431-8784
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics
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Call number:SPRINGER-2009-9780387922980:ONLINE Show nearby items on shelf
Title:Bayesian Computation with R [electronic resource]
Author(s): Jim Albert
Date:2009
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:There has been a dramatic growth in the development and application of Bayesian inferential methods. Some of this growth is due to the availability of powerful simulation-based algorithms to summarize posterior distributions.There has been also a gro wing interest in the use of the system R for statistical analyses. R's open source nature, free availability, and large number of contributor packages have made R the software of choice for many statisticiansin education and industry. Bayesian Computation with R introduces Bayesian modeling by the use of computation using the R language. The early chapters present the basic tenets of Bayesian thinking by use of familiar one andtwo-parameter inferential problems. Bayesian computational methods such as Lapl ace's method, rejection sampling, and the SIR algorithm are illustrated in the context of a random effects model. The construction and implementation ofMarkov Chain Monte Carlo (MCMC) methods is introduced. These simulation-based algorithms are implemente d for a variety of Bayesian applications such as normal and binary response regression, hierarchical modeling, order-restrictedinference, and robust modeling. Algorithms written in R are used to develop Bayesian tests and assess Bayesian models by use of the posterior predictive distribution. The use of R to interface with WinBUGS, a popular MCMC computinglanguage, is described with several illustrative examples. This book is a suitable companion book for an introductory course on Bayesian methods and is valuable to the statistical practitioner who wishes to learn more about the Rlanguage and Bayesian methodology. The LearnBayes package, written by the author and available from the CRAN website, contains all of the R functions described in the book. The s econd edition contains several new topics such as the useof mixtures of conjugate priors and the use of Zellners g priors to choose between models in linear regression. There are more illustrations o
Note:Springer eBooks
Contents:An introduction to R
Introduction to Bayesian thinking
Single
parameter models
Multiparameter models
Introduction to Bayesian computation
Markov chain Monte Carlo methods
Hierarchical modeling
Model comparison
Regression models
Gibbs sampling
Using R to interface with WinBUGS
ISBN:9780387922980
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer simulation , Computer science Mathematics , Visualization , Mathematical optimization , Mathematical statistics
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Call number:SPRINGER-2009-9780387781655:ONLINE Show nearby items on shelf
Title:Monte Carlo and Quasi-Monte Carlo Sampling [electronic resource]
Author(s): Christiane Lemieux
Date:2009
Edition:1
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:QuasiMonte Carlo methods have become an increasingly popular alternative to Monte Carlo methods over the last two decades. Their successful implementation on practical problems, especially in finance, has motivated thedevelopment of several new resea rch areas within this field to which practitioners and researchers from various disciplines currently contribute. This book presents essential tools for using quasiMonte Carlo sampling in practice.The first part of the book focuses on issues related to Mo nte Carlo methodsuniform and non-uniform random number generation, variance reduction techniquesbut the material is presented to prepare the readers for the next step,which is to replace the random sampling inherent to Monte Carlo by quasirandom sampling. The second part of the book deals with this next step. Several aspects of quasi-Monte Carlo methods are covered, including constructions,randomizations, the use of ANOVA decompositions, and the concept of effective dimension. The third part of the book i s devoted to applications in finance and more advanced statistical tools like Markov chain Monte Carlo and sequentialMonte Carlo, with a discussion of their quasiMonte Carlo counterpart. The prerequisites for reading this book are a basic knowledge of sta tistics and enough mathematical maturity to follow through the various techniques usedthroughout the book. This text is aimed at graduate students in statistics, management science, operations research, engineering, and applied mathematics. It should also be useful to practitioners who want to learn more about MonteCarlo and quasiMonte Carlo methods and researchers interested in an up-to-date guide to these methods. Christiane Lemieux is an Associate Professor and the Associate Chair for Actuarial Science in the Department of Statistics andActuarial Science at the University of Waterloo in Canada. She is an Associate of the Society of Actuaries and was the winner of a Young Researc
Note:Springer eBooks
Contents:The Monte Carlo Method
Sampling from Known Distributions
Pseudorandom Number Generators
Variance Reduction Techniques
QuasiMonte Carlo Constructions
Using QuasiMonte Carlo in Practice
Financial Applications
Beyond Numerical Integration
ISBN:9780387781655
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics
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Call number:SPRINGER-2008-9783540746867:ONLINE Show nearby items on shelf
Title:Computational Many-Particle Physics [electronic resource]
Author(s): H Fehske
R Schneider
A Weie
Date:2008
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Complicated many-particle problems abound in nature and in research alike. Plasma physics, statistical physics and condensed matter physics, as primary examples, are all heavily dependent on efficient methods for solving suchproblems. Addressing grad uate students and young researchers, this book presents an overview and introduction to state-of-the-art numerical methods for studying interacting classical and quantum many-particle systems. A broad range oftechniques and algorithms are covered, and emp hasis is placed on their implementation on modern high-performance computers
Note:Springer eBooks
Contents:Molecular Dynamics
to Molecular Dynamics
Wigner Function Quantum Molecular Dynamics
Classical Monte Carlo
The Monte Carlo Method, an Introduction
Monte Carlo Methods in Classical Statistical Physics
The Monte Carlo Method for Particle Transport Problems
Kinetic Modelling
The Particle
in
Cell Method
Gyrokinetic and Gyrofluid Theory and Simulation of Magnetized Plasmas
Semiclassical Approaches
Boltzmann Transport in Condensed Matter
Semiclassical Description of Quantum Many
Particle Dynamics in Strong Laser Fields
Quantum Monte Carlo
World
line and Deter
ISBN:9783540746867
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Physics, 0075-8450 : v739
Series:Physics and Astronomy (Springer-11651)
Keywords: Mathematical physics , Nuclear physics
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Call number:SPRINGER-2007-9783540360575:ONLINE Show nearby items on shelf
Title:Microscale and Nanoscale Heat Transfer [electronic resource]
Author(s): Sebastian Volz
Date:2007
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The book constitutes a particularly complete and original collection of ideas, models, numerical methods and experimental tools which will prove invaluable in the study of microscale and nanoscale heat transfer. It should be ofinterest to research sc ientists and thermal engineers who wish to carry out theoretical research or metrology in this field, but also to physicists concerned with the problems of heat transfer, or teachers requiring a solid foundationfor an undergraduate university course in th is area
Note:Springer eBooks
Contents:Part I: Basic Concepts
Laws of Macroscopic Heat Transfer and Their Limits
Transport in Dilute Media
Electrons and Phonons
Introduction to Radiative Transfer
Part II: Models and Numerical Methods
Solution of the Boltzmann Equation for Phonon Transport
Radiative Transfer on Short Length Scales
Monte Carlo Method
Molecular Dynamics
Part III: Experimental Methods and Applications
Scanning Thermal Microscopy
Optical Technique for Local Measurement
Hybrid Techniques and Multipurpose Microscopes
Electron
Phonon Interactions in Metals and Metallic Nanostructur
ISBN:9783540360575
Series:e-books
Series:SpringerLink (Online service)
Series:Topics in Applied Physics, 0303-4216 : v107
Series:Physics and Astronomy (Springer-11651)
Keywords: Thermodynamics
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Call number:SPRINGER-2007-9783540334019:ONLINE Show nearby items on shelf
Title:Theory of Defects in Semiconductors [electronic resource]
Author(s): David A Drabold
Stefan K Estreicher
Date:2007
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Semiconductor science and technology is the art of defect engineering. The theoretical modeling of defects has improved dramatically over the past decade. These tools are now applied to a wide range of materials issues: quantumdots, buckyballs, spint ronics, interfaces, amorphous systems, and many others. This volume presents a coherent and detailed description of the field, and brings together leaders in theoretical research. Today's state-of-the-art, aswell as tomorrows tools, are discussed: the sup ercell-pseudopotential method, the GW formalism,Quantum Monte Carlo, learn-on-the-fly molecular dynamics, finite-temperature treatments, etc. A wealth of applications are included, frompoint defects to wafer bonding or the propagation of dislocation
Note:Springer eBooks
Contents:1. Defect Theroy: An Armchair History
2. Supercell Methods for Defect Calculations
3. Marker
Method Calculations for Electrical Levels Using Gaussian
orbital Basis
sets
4. Dynamical Matrices and Free Energies
5. The Calculation of Free Energies in Semiconductors: Defects, Transitions and Phase Diagrams
6. Quantum Monte Carlo Techniques and Defects in Semiconductors
7. Quasiparticle Calculations for Point Defects at Semiconductor Surfaces
8. Multiscale Modelling of Defects in Semiconductors: A Novel Molecular Dynamics Scheme
9. Empirical Molecular Dynamics: Possibilities
ISBN:9783540334019
Series:e-books
Series:SpringerLink (Online service)
Series:Topics in Applied Physics, 0303-4216 : v104
Series:Physics and Astronomy (Springer-11651)
Keywords: Chemistry , Condensed matter , Physical optics , Optical materials
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Call number:SPRINGER-2007-9780817645731:ONLINE Show nearby items on shelf
Title:Molecular Gas Dynamics [electronic resource] : Theory, Techniques, and Applications
Author(s): Yoshio Sone
Date:2007
Publisher:Boston, MA : Birkhuser Boston
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This self-contained work is an up-to-date treatment of the basic theory of molecular gas dynamics and its various applications. Recent progress in the field has greatly enhanced the original theory and stimulated interesting andcritical gas dynamic p henomena and problems. This book, unique in the literature, presents working knowledge, theory, techniques, and typical phenomena in rarefied gases for theoretical development and applications. Basic theory isdeveloped in a systematic way and presented in a form easily applied to practical use. After presenting basic theory and various simple flows, such as unidirectional or quasi-unidirectional flows and flows around a sphere, the authordiscusses additional topics, including flows induced by temperature fields, which are typical in rarefied gases flows with evaporation and condensation and bifurcation of flows in rarefied gases. The appendix contains many usefulfundamental formulae, as well as an explanation of the theoretical background for the direct s imulation Monte Carlo (DSMC) method, easily accessible to nonmathematicians and not found elsewhere in the literature. Existence of the ghosteffect has made molecular gas dynamics indispensable to the study of a gas in the continuum limit, traditionally t reated by classical fluid dynamics. In this book, the ghost and non-NavierStokes effects are demonstrated for typicalexamplessuch as Bnard and TaylorCouette problemsin the context of a new framework. An infinitesimal curvature effect is also discussed, wi th a long-standing problem of the bifurcation of the plane Couette flow worked out asan example. Molecular Gas Dynamics is useful for those working in different communities where kinetic theory or fluid dynamics is important: graduate students, researcher s, and practitioners in theoretical physics, applied mathematics,and various branches of engineering. The work may be used as a self-study reference or as a textbook in graduate-level co
Note:Springer eBooks
Contents:Preface
Boltzmann Equation
Highly Rarefied Gas: Free Molecular Gas and Its Correction
Slightly Rarefied Gas: Asymptotic Theory of the Boltzmann System for Small Knudsen Numbers
Simple Flows
Flows Induced by Temperature Fields
Flows with Evaporation and Condensation
Bifurcation in the Half
Space Problem of Evaporation and Condensation
Ghost Effect and Bifurcation I: Bnard and TaylorCouette Problems
Ghost Effect and Bifurcation II: Ghost Effect of Infinitesimal Curvature and Bifurcation of the Plane Couette Flow
Appendix A. Supplement to the Boltzmann Equation
ISBN:9780817645731
Series:e-books
Series:SpringerLink (Online service)
Series:Modeling and Simulation in Science, Engineering and Technology
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Differential equations, partial , Computer science Mathematics , Mathematical physics , Gases , Hydraulic engineering
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Call number:SPRINGER-2007-9780387713854:ONLINE Show nearby items on shelf
Title:Bayesian Computation with R [electronic resource]
Author(s): Jim Albert
Date:2007
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:There has been a dramatic growth in the development and application of Bayesian inferential methods. Some of this growth is due to the availability of powerful simulation-based algorithms to summarize posterior distributions.There has been also a gro wing interest in the use of the system R for statistical analyses. R's open source nature, free availability, and large number of contributor packages have made R the software of choice for many statisticiansin education and industry. Bayesian Computation with R introduces Bayesian modeling by the use of computation using the R language. The early chapters present the basic tenets of Bayesian thinking by use of familiar one andtwo-parameter inferential problems. Bayesian computational methods such as Lapl ace's method, rejection sampling, and the SIR algorithm are illustrated in the context of a random effects model. The construction and implementation ofMarkov Chain Monte Carlo (MCMC) methods is introduced. These simulation-based algorithms are implemente d for a variety of Bayesian applications such as normal and binary response regression, hierarchical modeling, order-restrictedinference, and robust modeling. Algorithms written in R are used to develop Bayesian tests and assess Bayesian models by use of the posterior predictive distribution. The use of R to interface with WinBUGS, a popular MCMC computinglanguage, is described with several illustrative examples. This book is a suitable companion book for an introductory course on Bayesian methods and is valuable to the statistical practitioner who wishes to learn more about the Rlanguage and Bayesian methodology. The LearnBayes package, written by the author and available from the CRAN website, contains all of the R functions described in the book. Jim A lbert is Professor of Statistics at Bowling Green StateUniversity. He is Fellow of the American Statistical Association and is past editor of The American Statistician. His books include Ordinal Data Mo
Note:Springer eBooks
Contents:An introduction to R
Introduction to Bayesian thinking
Single
parameter models
Multiparameter models
Introduction to Bayesian computation
Markov chain Monte Carlo methods
Hierarchical modeling
Model comparision
Regression models
Gibbs sampling
Using R to interface with WinBUGS
ISBN:9780387713854
Series:e-books
Series:SpringerLink (Online service)
Series:Use R!
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer simulation , Computer science Mathematics , Visualization , Mathematical optimization , Mathematical statistics
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Call number:SPRINGER-2006-9780387357683:ONLINE Show nearby items on shelf
Title:Finite Mixture and Markov Switching Models [electronic resource]
Author(s): Sylvia Frhwirth-Schnatter
Date:2006
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The prominence of finite mixture modelling is greater than ever. Many important statistical topics like clustering data, outlier treatment, or dealing with unobserved heterogeneity involve finite mixture models in some way orother. The area of potent ial applications goes beyond simple data analysis and extends to regression analysis and to non-linear time series analysis using Markov switching models. For more than the hundred years since Karl Pearsonshowed in 1894 how to estimate the five parameters of a mixture of two normal distributions using the method of moments, statistical inference for finite mixture models has been a challenge to everybody who deals with them. In the pastten years, very powerful computational tools emerged for dealing with these models which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book reviews these techniques and covers the mostrecent advances in the field, among them bridge sampling techniques and reversible jump Ma rkov chain Monte Carlo methods. It is the first time that the Bayesian perspective of finite mixture modelling is systematically presented inbook form. It is argued that the Bayesian approach provides much insight in this context and is easily implemented in practice. Although the main focus is on Bayesian inference, the author reviews several frequentist techniques,especially selecting the number of components of a finite mixture model, and discusses some of their shortcomings compared to the Bayesian ap proach. The aim of this book is to impart the finite mixture and Markov switching approach tostatistical modelling to a wide-ranging community. This includes not only statisticians, but also biologists, economists, engineers, financial agents, market rese archer, medical researchers or any other frequent user of statisticalmodels. This book should help newcomers to the field to understand how finite mixture and Markov switching models are formulated, wha
Note:Springer eBooks
Contents:Finite Mixture Modelling
Statistical Inference for a Finite Mixture Model with Known Number of Components
Practical Bayesian Inference for A Finite Mixture Model With Known Number of Components
Statistical Inference for Finite Mixture Models Under Model Specification Uncertainty
Computational Tools for Bayesian Inference for Finite Mixture Models Under Model Specification Uncertainty
Finite Mixture Models With Normal Components
Data Analysis Based on Finite Mixtures
Finite Mixtures of Regression Models
Finite Mixture Models with Non
Normal Components
Finite Markov Mi
ISBN:9780387357683
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer science , Bioinformatics , Mathematical statistics , Econometrics , Psychometrics
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Call number:SPRINGER-2006-9780387312620:ONLINE Show nearby items on shelf
Title:Computer Algebra Recipes [electronic resource] : An Introductory Guide to the Mathematical Models of Science
Author(s): Richard H Enns
George C McGuire
Date:2006
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Computer algebra systems are revolutionizing the teaching, the learning, and the exploration of science. Not only can students and researchers work through mathematical models more efficiently and with fewer errors than withpencil and paper, they can also easily explore, both analytically and numerically, more complex and computationally intensive models. Aimed at science and engineering undergraduates at the sophomore/junior level, this introductoryguide to the mathematical models of science is fill ed with examples from a wide variety of disciplines, including biology, economics, medicine, engineering, game theory, mathematics, physics, and chemistry. The topics are organizedinto the Appetizers dealing with graphical aspects, the Entrees concentrati ng on symbolic computation, and the Desserts illustrating numerical simulation. The heart of the text is a large number of computer algebra recipes based on theMaple 10 software system. These have been designed not only to provide tools for problem solvin g, but also to stimulate the readers imagination. Associated with each recipe is a scientific model or method and an interesting oramusing story (accompanied with a thought-provoking quote) that leads the reader through the various steps of the recipe. Th is text is the first of two volumes. The advanced guide, aimed at junior/senior/graduate level students,deals with more advanced differential equation models
Note:Springer eBooks
Contents:The Appetizers
The Pictures of Science
Deriving Model Equations
The Entrees
Algebraic Models. Part I
Algebraic Models. Part II
Linear ODE Models
Difference Equation Models
The Desserts
Monte Carlo Methods
Fractal Patterns
ISBN:9780387312620
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Algebra Data processing , Computer simulation , Computer software , Mathematical physics , Engineering mathematics
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Call number:SPRINGER-2005-9783540276890:ONLINE Show nearby items on shelf
Title:Stochastic Numerics for the Boltzmann Equation [electronic resource]
Author(s): Sergej Rjasanow
Wolfgang Wagner
Date:2005
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Stochastic numerical methods play an important role in large scale computations in the applied sciences. The first goal of this book is to give a mathematical description of classical direct simulation Monte Carlo (DSMC)procedures for rarefied gases, using the theory of Markov processes as a unifying framework. The second goal is a systematic treatment of an extension of DSMC, called stochastic weighted particle method. This method includes severalnew features, which are introduced for the purpose of variance reduction (rare event simulation). Rigorous convergence results as well as detailed numerical studies are presented
Note:Springer eBooks
ISBN:9783540276890
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Computational Mathematics, 0179-3632 : v37
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Differential equations, partial , Numerical analysis , Distribution (Probability theory) , Mathematical physics
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Call number:SPRINGER-2005-9780387290539:ONLINE Show nearby items on shelf
Title:Nonparametric Monte Carlo Tests and Their Applications [electronic resource]
Author(s): Lixing Zhu
Date:2005
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:A fundamental issue in statistical analysis is testing the fit of a particular probability model to a set of observed data. Monte Carlo approximation to the null distribution of the test provides a convenient and powerful means oftesting model fit. N onparametric Monte Carlo Tests and Their Applications proposes a new Monte Carlo-based methodology to construct this type of approximation when the model is semistructured. When there are no nuisance parameters tobe estimated, the nonparametric Monte Carl o test can exactly maintain the significance level, and when nuisance parameters exist, this method can allow the test to asymptotically maintain the level. The author addresses both appliedand theoretical aspects of nonparametric Monte Carlo tests. The n ew methodology has been used for model checking in many fields of statistics, such as multivariate distribution theory, parametric and semiparametric regression models,multivariate regression models, varying-coefficient models with longitudinal data, hete roscedasticity, and homogeneity of covariance matrices. This book will be of interest to both practitioners and researchers investigatinggoodness-of-fit tests and resampling approximations. Every chapter of the book includes algorithms, simulations, and t heoretical deductions. The prerequisites for a full appreciation of the book are a modest knowledge of mathematicalstatistics and limit theorems in probability/empirical process theory. The less mathematically sophisticated reader will find Chapters 1, 2 and 6 to be a comprehensible introduction on how and where the new method can apply and therest of the book to be a valuable reference for Monte Carlo test approximation and goodness-of-fit tests. Lixing Zhu is Associate Professor of Statistics at the Uni versity of Hong Kong. He is a winner of the Humboldt Research Award atAlexander-von Humboldt Foundation of Germany and an elected Fellow of the Institute of Mathematical Statistics.>
Note:Springer eBooks
Contents:Monte Carlo Tests
Testing for Multivariate Distributions
Asymptotics of Goodness
of
fit Tests for Symmetry
A Test of Dimension
Reduction Type for Regressions
Checking the Adequacy of a Partially Linear Model
Model Checking for Multivariate Regression Models
Heteroscedasticity Tests for Regressions
Checking the Adequacy of a Varying
Coefficients Model
On the Mean Residual Life Regression Model
Homegeneity Testing for Covariance Matrices
ISBN:9780387290539
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Statistics, 0930-0325 : v182
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics
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Call number:SPRINGER-2004-9783662095102:ONLINE Show nearby items on shelf
Title:Progress in Industrial Mathematics at ECMI 2002
Author(s):
Date:2004
Size:1 online resource (409 p.)
Note:10.1007/978-3-662-09510-2
Contents:Mathematical Modeling is a Source of Novel Mathematical Problems -- Parameter Identification in Industrial Problems via Iterative Regularization Methods -- Mathematics of Enhanced Oil Recovery -- Business Modelling. Languages and
Tools -- Modelling Tumour Growth and Progression -- Interaction of Viscous Mean Flows and Surface Waves at Low Viscosity -- Modified FEM for Fibre-Fluid Interactions -- Numerical Investigation of the Geometrical Factor for Simulating
the Drying of Wood -- Phase Plane Analysis of Web Drying -- Parameters Identification for Wood Drying -- Numerical Methods in the Simulation of Vehicle-Guideway Interaction -- Parameter Optimization in Mechanical Multibody Systems and
Linearized Runge-Kutta Methods -- Using AD-generated Derivatives in Optimal Control of an Industrial Robot -- Applications to Traffic Breakdown on Highways -- Runge-Kutta-Nyström-Methods with Maximized Stability Domain for Stiff
Mechanical Systems -- Free Boundary Problems Describing Two-Dimensional Pulse Recycling and Motion in Semiconductors -- Mobility for Silicon Semiconductor Derived from the Hydrodynamical Model Based on the Maximum Entropy Principle --
Random Domain-Relocation Times in Semiconductor Superlattices: A Stochastic Discrete Drift-Diffusion Approach -- A Priori Estimates for Multiphysics Models in Electric Circuit Design -- Preconditioned Splitting in Dynamic Iteration
Schemes for Coupled DAE Systems in RC Network Design -- Augmented Lagrangian Algorithm for Optimizing Analog Circuit Design -- Simulating Multi-tone Free-running Oscillators with Optimal Sweep Following -- Jacobi-Davidson Methods and
Preconditioning with Applications in Pole-zero Analysis -- Development and Comparison of Formulas for Scaling ANN Inputs and Outputs in RF-Modeling Applications -- Reduced Order Modelling — Methods and Constraints -- Ghost Field
Gauging Used in Electrodynamic Simulation -- Option Pricing Using Stochastic Volatility Models -- Mathematical Model for Gravitational Cascade Separation of Pourable Materials at Identical Stages of a Classifier -- Parallel Iterative
Solvers for Sparse Linear Systems in Circuit Simulation -- Conservative Averaging Method for Solutions of Inverse Problems for Heat Equation -- Creation of Temperature Field in a Finite Cylinder by Alternated Electromagnetic Force -- A
Finite Element Method for Parabolic Equations -- Reduction of a Mathematical Model for Polymer Crystallization -- Asymptotic and Numerical Aspects of a Nonlinear Singular Integro-Differential Equation for Dryout in a LMFBR Boiler Tube
-- Geostatistics: An Overview of Estimation and Simulation Methods for Oil Reservoirs and Basin Modelling -- Global Uncertainty and Sensitivity Analysis and Neighbourhoods -- A Mathematical Model for Tonometry -- Modelling Capillary
Pressure in a Streamline Reservoir Simulator Using Operator Splitting -- Electromagnetic Simulations in the Electronics Industry -- Reduction of a Non—Linear Parabolic Initial—Boundary Value Problem to Cauchy Problem for a System of
ODEs -- Recent Applications of Multipole Expansions in Computational Electromagnetics -- Examples of Asymptotical Analysis of Hyperbolic Equations -- Monte Carlo Valuation of American Options -- On the Frame — Invariant Description of
the Phase Space of the Folgar—Tucker Equation -- Simulating Bass Loudspeakers Requires Nonlinear Acoustics — a Second Order Correction to the Helmholtz Equation -- A Mathematical Model for Hammocking of a Bandage on a Limb --
Probabilistic Analysis of DAX High Frequency Data -- Optimal and Robust Damping Control for Semi-Active Vehicle Suspension -- A Fast Finite Difference Method for Elliptic PDEs in Domains with Non-Grid Aligned Boundaries with
Application to 3D Linear Elasticity -- Analysis of a Model for Twin-Wire Forming -- Coherent Dynamics of Excitable and Coupled ?-Cells -- A Mathematical Model of the Cardiovascular System -- Mathematical Modelling of the Drawing of
Spun Capillary Tubes -- Mathematical Modelling of CO-oxidation on Modified Pt-Catalyst -- Mathematical Models for Impinging Jets -- Relations Between the Motion-Responses Caused by Fixed and Moving Loads Acting on Discretely Supported
Strings and Beams
ISBN:9783662095102
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:The European Consortium for Mathematics in Industry: 5
Keywords: Mathematics , Chemometrics , Applied mathematics , Engineering mathematics , Economics, Mathematical , Computer mathematics , Mathematical optimization , Mathematics , Applications of Mathematics , Computational Mathematics and Numerical Analysis , Optimization , Math. Applications in Chemistry , Appl.Mathematics/Computational Methods of Engineering , Quantitative Finance
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Call number:SPRINGER-2004-9783642592935:ONLINE Show nearby items on shelf
Title:Computer Simulation Studies in Condensed-Matter Physics XVI Proceedings of the Fifteenth Workshop, Athens, GA, USA, February 24–28, 2003
Author(s):
Date:2004
Edition:1
Size:1 online resource (258 p.)
Note:10.1007/978-3-642-59293-5
Contents:1 Computer Simulation Studies in Condensed Matter Physics: An Introduction -- I Nonequilibrium Phenomena -- 2. Fast Coarsening and Steady States in a Low-Dimensional Driven System -- 3. A Nonequilibrium Lattice Gas of Two-species:
Monte Carlo Investigations -- 4. Stochastic Growth in a Small World -- 5. Flicker Noise in a Model of Coevolving Biological Populations -- II Quantum Phenomena -- 6. Physical and Computational Aspects of Density Functional Spin
Dynamics -- 7. Finite Temperature Simulation Based on Lanczos Algorithm for Low-Dimensional Quantum Systems -- 8. Quantum Phase Transitions of Quasi-One-Dimensional Heisenberg Antiferromagnets -- 9. Multi-hole Tunneling between Charge
Domains in Doped Antiferromagnets -- 10. Decoherence in Quantum Spin Systems -- 11. Quantum Computing Simulation using the Auxiliary Field Decomposition -- III Phase Transitions -- 12. Quenched Disorder Distributions in
Three-Dimensional Diluted Ferromagnets -- 13. Weak Universality of Spin Glasses in Three Dimensions -- 14. Critical Exponents of the Two Dimensional Melting -- 15. Numerical Study of Critical Exponents for Kosterlitz—Thouless
Transition Systems -- 16. Critical Wetting and Interface Localization—Derealization Transition in a Double Wedge -- IV Soft Condensed Matter -- 17. Effect of Packing Parameter on Amphiphilic Self-Assembly: A Brownian Dynamics Study --
18. The Droplet Evaporation/Condensation Transition in a Finite Volume -- 19. Configurational Bias Monte Carlo Applied to Lipid Membranes in the Semi-grand Ensemble to Speed Up Mixing -- 20. Folding Polymer Chains -- 21. Polymer
Collapse in High Dimensions: Monte Carlo Simulation of Lattice Models -- 22. Computer Simulation of Polymers: Physics and Methods from Specific to Universal -- V Methods and Pedagogy -- 23. Using Simulations to Teach Statistical
Physics -- 24. Visualization of Melting Simulations -- 25. Network Algorithms and Critical Manifolds in Disordered Systems -- 26. Random Graphs as Building Blocks for a Network Model -- 27. Generalized Probability-Changing Algorithm --
28. Adaptive Integration Method -- VI Simulations of Materials -- 29. Lattice Instabilities of Perovskite Oxides from First Principles -- 30. Monte Carlo Simulations of Metal Monoatomic Layers -- 31. Molecular Dynamics Simulation of
Nanoindentation -- List of Contributors
ISBN:9783642592935
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Springer Proceedings in Physics: 95
Keywords: Physics , Condensed matter , Physics , Condensed Matter Physics , Theoretical, Mathematical and Computational Physics
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Call number:SPRINGER-2004-9783642187865:ONLINE Show nearby items on shelf
Title:Option Theory with Stochastic Analysis An Introduction to Mathematical Finance
Author(s): Fred Espen Benth
Date:2004
Size:1 online resource (162 p.)
Note:10.1007/978-3-642-18786-5
Contents:1 Introduction -- 1.1 An Introduction to Options in Finance -- 1.2 Some Useful Material from Probability Theory -- 2 Statistical Analysis of Data from the Stock Market -- 2.1 The Black & Scholes Model -- 2.2 Logarithmic Returns from
Stocks -- 2.3 Scaling Towards Normality -- 2.4 Heavy-Tailed and Skewed Logreturns -- 2.5 Logreturns and the Normal Inverse Gaussian Distribution -- 2.6 An Alternative to the Black & Scholes Model -- 2.7 Logreturns and Autocorrelation
-- 2.8 Conclusions Regarding the Choice of Stock Price Model -- 3 An Introduction to Stochastic Analysis -- 3.1 The Itô Integral -- 3.2 The Itô Formula -- 3.3 Geometric Brownian Motion as the Solution of a Stochastic Differential
Equation -- 3.4 Conditional Expectation and Martingales -- 4 Pricing and Hedging of Contingent Claims -- 4.1 Motivation from One-Period Markets -- 4.2 The Black & Scholes Market and Arbitrage -- 4.3 Pricing and Hedging of Contingent
Claims X= f(S(T)) -- 4.4 The Girsanov Theorem and Equivalent Martingale Measures -- 4.5 Pricing and Hedging of General Contingent Claims -- 4.6 The Markov Property and Pricing of General Contingent Claims -- 4.7 Contingent Claims on
Many Underlying Stocks -- 4.8 Completeness, Arbitrage and Equivalent Martingale Measures -- 4.9 Extensions to Incomplete Markets -- 5 Numerical Pricing and Hedging of Contingent Claims -- 5.1 Pricing and Hedging with Monte Carlo
Methods -- 5.2 Pricing and Hedging with the Finite Difference Method -- A Solutions to Selected Exercises -- References
ISBN:9783642187865
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Finance , Economics, Mathematical , Probabilities , Statistics , Finance , Finance, general , Probability Theory and Stochastic Processes , Quantitative Finance , Statistics for Business/Economics/Mathematical Finance/Insurance
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Call number:SPRINGER-2004-9783642187568:ONLINE Show nearby items on shelf
Title:Multiscale Modelling and Simulation
Author(s):
Date:2004
Size:1 online resource (141 p.)
Note:10.1007/978-3-642-18756-8
Contents:I Mathematical Methods -- Some Recent Progress in Multiscale Modeling -- Homogenization Method for Transport of DNA Particles in Heterogeneous Arrays -- Metastability, conformation dynamics, and transition pathways in complex systems
-- Nonlinear Dynamics Analysis through Molecular Dynamics Simulations -- Exploration of coarse free energy surfaces templated on continuum numerical methods -- Damping factors for the gap-tooth scheme -- II Materials Science --
Multiscale Aspects of Polymer Simulations -- Polymers near a Surface: An ab initio Density Functional based Multiscale Modeling Approach -- Dual Resolution Molecular Simulation of Bisphenol-A Polycarbonate Adsorption onto Nickel (111):
Chain Length Effects -- Stress and energy flow field near a rapidly propagating mode I crack -- A Peierls Criterion for Deformation Twinning at a Mode II Crack -- III Physics/Chemistry/Fluid Dynamics/Biology -- Simulation of Transport
in Partially Miscible Binary Fluids: Combination of Semigrandcanonical Monte Carlo and Molecular Dynamics Methods -- Computer simulations of SiO2 and GeO2 -- Large Scale Density Functional Calculations -- Dispersion corrected density
functionals applied to the water naphthalene cluster -- Flow of Aqueous Solutions in Carbon Nanotubes -- Continuum-particle hybrid methods for dense fluids -- Dissipative Particle Dynamics for Modeling Complex Fluidics -- Population
balance modeling of synthesis of nanoparticles in aerosol flame reactors -- Modelling gene expression using stochastic simulation -- Color Plates
ISBN:9783642187568
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Lecture Notes in Computational Science and Engineering: 39
Keywords: Mathematics , Chemometrics , Computer mathematics , Mathematical models , Applied mathematics , Engineering mathematics , Mathematics , Mathematical Modeling and Industrial Mathematics , Computational Mathematics and Numerical Analysis , Appl.Mathematics/Computational Methods of Engineering , Math. Applications in Chemistry
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Call number:SPRINGER-2004-9783642187438:ONLINE Show nearby items on shelf
Title:Monte Carlo and Quasi-Monte Carlo Methods 2002 Proceedings of a Conference held at the National University of Singapore, Republic of Singapore, November 25–28, 2002
Author(s):
Date:2004
Size:1 online resource (460 p.)
Note:10.1007/978-3-642-18743-8
Contents:Invited Papers -- Finance: A Fertile Field for Applications of MC and QMC -- How Many Random Bits Do We Need for Monte Carlo Integration? -- On Tractability of Weighted Integration for Certain Banach Spaces of Functions -- Polynomial
Integration Lattices -- Approximate Bayesian Computation and MCMC -- New Challenges for the Simulation of Stochastic Processes -- Stochastic Models and Monte Carlo Algorithms for Boltzmann Type Equations -- Digital Nets, Duality, and
Algebraic Curves -- Contributed Papers -- Generalized Mersenne Prime Number and Its Application to Random Number Generation -- Constructing Good Lattice Rules with Millions of Points -- Lattice Structure of Nonlinear Pseudorandom
Number Generators in Parts of the Period -- Simulation for American Options: Regression Now or Regression Later? -- Perturbation Monte Carlo Methods for the Solution of Inverse Problems -- Quantum Boolean Summation with Repetitions in
the Worst-Average Setting -- The Strong Tractability of Multivariate Integration Using Lattice Rules -- Minimizing Effective Dimension Using Linear Transformation -- Component by Component Construction of Rank-1 Lattice Rules Having
O(n-1(ln(n))d) Star Discrepancy -- Stratification by Rank-1 Lattices -- Walsh Series Analysis of the Star Discrepancy of Digital Nets and Sequences -- Quasi-Monte Carlo Methods for Estimating Transient Measures of Discrete Time Markov
Chains -- Quasi-Monte Carlo Methods for Elliptic BVPs -- Stable Connectivity of Networks and Its Monte Carlo Estimation -- Random Number Generators Based on Linear Recurrences in % MathType!MTEF!2!1!+- %
feaagaart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn % hiov2DGi1BTfMBaeXafv3ySLgzGmvETj2BSbWexLMBb50ujbqegm0B % 1jxALjharqqr1ngBPrgifHhDYfgasaacH8srps0lbbf9q8WrFfeuY- % Hhbbf9v8qqaqFr0xc9pk0xbba9q8WqFfea0-yr0RYxir-Jbba9q8aq %
0-yq-He9q8qqQ8frFve9Fve9Ff0dmeaabaqaciaacaGaaeqabaWaae % aaeaaakeaatuuDJXwAK1uy0HMmaeXbfv3ySLgzG0uy0HgiuD3BaGqb % biab-vi8gnaaBaaaleaacaaIYaWaaWbaaWqabeaaryqr1ngBPrgaiy % GacqGF3bWDaaaaleqaaaaa!4C2E! $$ \mathbb{F}_{2^w } $$ -- Using
Quasi-Monte Carlo Scenarios in Risk Management -- Adaptive Quasi-Monte Carlo Integration Based on MISER and VEGAS -- When Does Monte Carlo Depend Polynomially on the Number of Variables? -- A New Adaptive Method for Geometric
Convergence -- Polynomial Arithmetic Analogue of Hickernell Sequences
ISBN:9783642187438
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Mathematics , Applied mathematics , Engineering mathematics , Economics, Mathematical , Computer mathematics , Probabilities , Statistics , Mathematics , Probability Theory and Stochastic Processes , Computational Mathematics and Numerical Analysis , Applications of Mathematics , Statistics for Business/Economics/Mathematical Finance/Insurance , Quantitative Finance
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Call number:SPRINGER-2004-9783642171031:ONLINE Show nearby items on shelf
Title:Classification, Clustering, and Data Mining Applications Proceedings of the Meeting of the International Federation of Classification Societies (IFCS), Illinois Institute of Technology, Chicago, 15–18 July 2004
Author(s):
Date:2004
Size:1 online resource (658 p.)
Note:10.1007/978-3-642-17103-1
Contents:I New Methods in Cluster Analysis -- Thinking Ultrametrically -- Clustering by Vertex Density in a Graph -- Clustering by Ant Colony Optimization -- A Dynamic Cluster Algorithm Based on Lr Distances for Quantitative Data -- The Last
Step of a New Divisive Monothetic Clustering Method: the Gluing-Back Criterion -- Standardizing Variables in K-means Clustering -- A Self-Organizing Map for Dissimilarity Data -- Another Version of the Block EM Algorithm -- Controlling
the Level of Separation of Components in Monte Carlo Studies of Latent Class Models -- Fixing Parameters in the Constrained Hierarchical Classification Method: Application to Digital Image Segmentation -- New Approaches for
Sum-of-Diameters Clustering -- Spatial Pyramidal Clustering Based on a Tessellation -- II Modern Nonparametrics -- Relative Projection Pursuit and its Application -- Priors for Neural Networks -- Combining Models in Discrete
Discriminant Analysis Through a Committee of Methods -- Phoneme Discrimination with Functional Multi-Layer Perceptrons -- PLS Approach for Clusterwise Linear Regression on Functional Data -- On Classification and Regression Trees for
Multiple Responses -- Subsetting Kernel Regression Models Using Genetic Algorithm and the Information Measure of Complexity -- Cherry-Picking as a Robustness Tool -- III Classification and Dimension Reduction -- Academic Obsessions and
Classification Realities: Ignoring Practicalities in Supervised Classification -- Modified Biplots for Enhancing Two-Class Discriminant Analysis -- Weighted Likelihood Estimation of Person Locations in an Unfolding Model for Polytomous
Responses -- Classification of Geospatial Lattice Data and their Graphical Representation -- Degenerate Expectation-Maximization Algorithm for Local Dimension Reduction -- A Dimension Reduction Technique for Local Linear Regression --
Reducing the Number of Variables Using Implicative Analysis -- Optimal Discretization of Quantitative Attributes for Association Rules -- IV Symbolic Data Analysis -- Clustering Methods in Symbolic Data Analysis -- Dependencies in
Bivariate Interval-Valued Symbolic Data -- Clustering of Symbolic Objects Described by Multi-Valued and Modal Variables -- A Hausdorff Distance Between Hyper-Rectangles for Clustering Interval Data -- Kolmogorov-Smirnov for Decision
Trees on Interval and Histogram Variables -- Dynamic Cluster Methods for Interval Data Based on Mahalanobis Distances -- A Symbolic Model-Based Approach for Making Collaborative Group Recommendations -- Probabilistic Allocation of
Aggregated Statistical Units in Classification Trees for Symbolic Class Description -- Building Small Scale Models of Multi-Entity Databases by Clustering -- V Taxonomy and Medicine -- Phylogenetic Closure Operations and Homoplasy-Free
Evolution -- Consensus of Classification Systems, with Adams’ Results Revisited -- Symbolic Linear Regression with Taxonomies -- Determining Horizontal Gene Transfers in Species Classification: Unique Scenario -- Active and Passive
Learning to Explore a Complex Metabolism Data Set -- Mathematical and Statistical Modeling of Acute Inflammation -- Combining Functional MRI Data on Multiple Subjects -- Classifying the State of Parkinsonism by Using Electronic Force
Platform Measures of Balance -- Subject Filtering for Passive Biometric Monitoring -- VI Text Mining -- Mining Massive Text Data and Developing Tracking Statistics -- Contributions of Textual Data Analysis to Text Retrieval --
Automated Resolution of Noisy Bibliographic References -- Choosing the Right Bigrams for Information Retrieval -- A Mixture Clustering Model for Pseudo Feedback in Information Retrieval -- Analysis of Cross-Language Open-Ended
Questions Through MFACT -- Inferring User’s Information Context from User Profiles and Concept Hierarchies -- Database Selection for Longer Queries -- VII Contingency Tables and Missing Data -- An Overview of Collapsibility --
Generalized Factor Analyses for Contingency Tables -- A PLS Approach to Multiple Table Analysis -- Simultaneous Rowand Column Partitioning in Several Contingency Tables -- Missing Data and Imputation Methods in Partition of Variables
-- The Treatment of Missing Values and its Effect on Classifier Accuracy -- Clustering with Missing Values: No Imputation Required
ISBN:9783642171031
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Culture , Library science , Data structures (Computer science) , Mathematical statistics , Computers , Statistics , Cultural and Media Studies , Library Science , Statistical Theory and Methods , Probability and Statistics in Computer Science , Information Systems and Communication Service , Data Structures , Statistics for Life Sciences, Medicine, Health Sciences
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Call number:SPRINGER-2004-9783642170294:ONLINE Show nearby items on shelf
Title:Model Reduction Methods for Vector Autoregressive Processes
Author(s): Ralf Brüggemann
Date:2004
Size:1 online resource (218 p.)
Note:10.1007/978-3-642-17029-4
Contents:1 Introduction -- 1.1 Objective of the Study -- 1.2 Outline of the Study -- 2 Model Reduction in VAR Models -- 2.1 The VAR Modeling Framework -- 2.2 Specification of Subset VAR Models -- 2.3 Monte Carlo Comparison -- 2.4 Summary -- 3
Model Reduction in Cointegrated VAR Models -- 3.1 The Cointegrated VAR Modeling Framework -- 3.2 Modeling Cointegrated VAR Processes -- 3.3 Data Based Model Reduction -- 3.4 Evaluation of Model Reduction Method -- 3.5 Summary -- 3.A
DOP Parameters and Properties -- 4 Model Reduction and Structural Analysis -- 4.1 The Structural VAR Modeling Framework -- 4.2 Estimation of Structural VAR Models -- 4.3 Monte Carlo Experiments -- 4.4 Summary -- 4.A Time Series Plots
-- 4.B DGP Parameters -- 5 Empirical Applications -- 5.1 The Effects of Monetary Policy Shocks -- 5.2 Sources of German Unemployment -- 5.3 Summary -- 5.A Data Sources -- 5.B Two Cointegrating Vectors -- 5.C VECM Estimates -- 6
Concluding Remarks and Outlook -- 6.1 Summary -- 6.2 Extensions -- Index of Notation -- List of Figures -- List of Tables
ISBN:9783642170294
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Lecture Notes in Economics and Mathematical Systems: 536
Keywords: Mathematics , Probabilities , Statistics , Econometrics , Mathematics , Probability Theory and Stochastic Processes , Econometrics , Statistics for Business/Economics/Mathematical Finance/Insurance
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Call number:SPRINGER-2004-9781468493931:ONLINE Show nearby items on shelf
Title:Feynman-Kac Formulae Genealogical and Interacting Particle Systems with Applications
Author(s): Pierre Del Moral
Date:2004
Size:1 online resource (556 p.)
Note:10.1007/978-1-4684-9393-1
Contents:1 Introduction -- 1.1 On the Origins of Feynman-Kac and Particle Models -- 1.2 Notation and Conventions -- 1.3 Feynman-Kac Path Models -- 1.4 Motivating Examples -- 1.5 Interacting Particle Systems -- 1.6 Sequential Monte Carlo
Methodology -- 1.7 Particle Interpretations -- 1.8 A Contents Guide for the Reader -- 2 Feynman-Kac Formulae -- 2.1 Introduction -- 2.2 An Introduction to Markov Chains -- 2.4 Structural Stability Properties -- 2.5 Distribution Flows
Models -- 2.6 Feynman-Kac Models in Random Media -- 2.7 Feynman-Kac Semigroups -- 3 Genealogical and Interacting Particle Models -- 3.1 Introduction -- 3.2 Interacting Particle Interpretations -- 3.3 Particle models with Degenerate
Potential -- 3.4 Historical and Genealogical Tree Models -- 3.5 Particle Approximation Measures -- 4 Stability of Feynman-Kac Semigroups -- 4.1 Introduction -- 4.2 Contraction Properties of Markov Kernels -- 4.3 Contraction Properties
of Feynman-Kac Semigroups -- 4.4 Updated Feynman-Kac Models -- 5 Invariant Measures and Related Topics -- 5.1 Introduction -- 5.2 Existence and Uniqueness -- 5.3 Invariant Measures and Feynman-Kac Modeling -- 5.4 Feynman-Kac and
Metropolis-Hastings Models -- 5.5 Feynman-Kac-Metropolis Models -- 6 Annealing Properties -- 6.1 Introduction -- 6.2 Feynman-Kac-Metropolis Models -- 6.3 Feynman-Kac Trapping Models -- 7 Asymptotic Behavior -- 7.1 Introduction -- 7.2
Some Preliminaries -- 7.3 Inequalities for Independent Random Variables -- 7.4 Strong Law of Large Numbers -- 8 Propagation of Chaos -- 8.1 Introduction -- 8.2 Some Preliminaries -- 8.3 Outline of Results -- 8.4 Weak Propagation of
Chaos -- 8.5 Relative Entropy Estimates -- 8.6 A Combinatorial Transport Equation -- 8.7 Asymptotic Properties of Boltzmann-Gibbs Distributions -- 8.8 Feynman-Kac Semigroups -- 9 Central Limit Theorems -- 9.1 Introduction -- 9.2 Some
Preliminaries -- 9.3 Some Local Fluctuation Results -- 9.4 Particle Density Profiles -- 9.5 A Berry-Esseen Type Theorem -- 9.6 A Donsker Type Theorem -- 9.7 Path-Space Models -- 9.8 Covariance Functions -- 10 Large-Deviation Principles
-- 10.1 Introduction -- 10.2 Some Preliminary Results -- 10.3 Crámer’s Method -- 10.4 Laplace-Varadhan’s Integral Techniques -- 10.5 Dawson-Gärtner Projective Limits Techniques -- 10.6 Sanov’s Theorem -- 10.7 Path-Space and Interacting
Particle Models -- 10.8 Particle Density Profile Models -- 11 Feynman-Kac and Interacting Particle Recipes -- 11.1 Introduction -- 11.2 Interacting Metropolis Models -- 11.3 An Overview of some General Principles -- 11.4 Descendant and
Ancestral Genealogies -- 11.5 Conditional Explorations -- 11.6 State-Space Enlargements and Path-Particle Models -- 11.7 Conditional Excursion Particle Models -- 11.8 Branching Selection Variants -- 11.9 Exercises -- 12 Applications --
12.1 Introduction -- 12.2 Random Excursion Models -- 12.3 Change of Reference Measures -- 12.4 Spectral Analysis of Feynman-Kac-Schrödinger Semigroups -- 12.5 Directed Polymers Simulation -- 12.6 Filtering/Smoothing and Path estimation
-- References
ISBN:9781468493931
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Mathematics , Mathematical models , Operations research , Management science , Probabilities , Statistical physics , Dynamical systems , Statistics , Applied mathematics , Engineering mathematics , Mathematics , Probability Theory and Stochastic Processes , Statistical Physics, Dynamical Systems and Complexity , Mathematical Modeling and Industrial Mathematics , Operations Research, Management Science , Appl.Mathematics/Computational Methods of Engineering , Statistical Theory and Methods
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