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SPIRES-BOOKS: FIND KEYWORD MARKOV PROCESSES *END*INIT* use /tmp/qspiwww.webspi1/13343.63 QRY 131.225.70.96 . find keyword markov processes ( in books using www Cover
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Call number:9783319500386:ONLINE Show nearby items on shelf
Title:Stochastic Modeling
Author(s): Nicolas Lanchier
Date:2017
Size:1 online resource (XIII, 303 p. 63 illus., 6 illus. in color p.)
Contents:1. Basics of Measure and Probability Theory -- 2. Distribution and Conditional Expectation -- 3. Limit Theorems -- 4. Stochastic Processes: General Definition -- 5. Martingales -- 6. Branching Processes -- 7. Discrete-time Markov
Chains -- 8. Symmetric Simple Random Walks -- 9. Poisson Point and Poisson Processes -- 10. Continuous-time Markov Chains -- 11. Logistic Growth Process -- 12. Wright-Fisher and Moran Models -- 13. Percolation Models -- 14. Interacting
Particle Systems -- 15. The Contact Process -- 16. The Voter Model -- 17. Numerical Simulations in C and Matlab
ISBN:9783319500386
Series:eBooks
Series:Springer eBooks
Series:Springer 2017 package
Keywords: Mathematics , Mathematical models , Probabilities , Mathematics , Probability Theory and Stochastic Processes , Mathematical Modeling and Industrial Mathematics
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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:1848218397:ONLINE Show nearby items on shelf
Title:Numerical Methods for Simulation and Optimizationof Piecewise Deterministic Markov Processes: Application to Reliability
Author(s): de Saporta
Date:2016
Publisher:Wiley-ISTE
Size:1 online resource (299 p.)
ISBN:9781848218390
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Mathematics
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Call number:1848211678:ONLINE Show nearby items on shelf
Title:Markov Decision Processes & Artificial Intelligence
Author(s): Sigaud
Date:2010
Publisher:Wiley-ISTE
Size:1 online resource (481 p.)
ISBN:9781848211674
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Electrical & Electronics Engineering
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Call number:0471619779:ONLINE Show nearby items on shelf
Title:Markov Decision Processes: Discrete Stochastic Dynamic Programming
Author(s): Puterman
Date:1994
Publisher:Wiley-Interscience
Size:1 online resource (673 p.)
ISBN:9780471619772
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0471081868:ONLINE Show nearby items on shelf
Title:Markov Processes: Characterization and Convergence
Author(s): Ethier
Date:1986
Publisher:Wiley
Size:1 online resource (529 p.)
ISBN:9780471081869
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0470772719:ONLINE Show nearby items on shelf
Title:Markov Processes and Applications - Algorithms, Networks, Genome and Finance
Author(s): Pardoux
Date:2008
Publisher:Wiley
Size:1 online resource (323 p.)
ISBN:9780470772713
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Mathematics
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Call number:SPRINGER-2016-9783662497685:ONLINE Show nearby items on shelf
Title:Recueil de Modèles Aléatoires
Author(s): Djalil Chafai
Date:2016
Size:1 online resource (398 p.)
Note:10.1007/978-3-662-49768-5
Contents:Avant-propos -- Pile, face, coupons -- Marches aléatoires -- Branchement et processus de Galton-Watson -- Permutations, partitions, et graphes -- Mesures de Gibbs -- Agrégation limitée par diffusion interne -- Chaînes de Markov cachées -- Cha nes de Markov cachées -- Algorithme EM et mélanges -- Urnes d’Ehrenfest -- Records, extrêmes, et recrutements -- File d’attente M/M/Infini -- Modèle de Wright-Fisher -- Généalogies et coalescence -- Restaurants chinois -- Renforcement -- Percol ation -- Croissance et fragmentation -- Ruine d’une compagnie d’assurance -- Polymères dirigés en environnement aléatoire -- Problème du voyageur de commerce -- Matrices aléatoires -- Naissances et assassinats -- Modèle du télégraphe -- Probl me de Dirichlet -- Processus d’Ornstein-Uhlenbeck -- Modèles de diffusion cinétique -- Des chaînes de Markov aux processus de diffusion -- Suggestions bibliographiques -- Littérature -- Index -- Principales notations et abréviations
ISBN:9783662497685
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Mathématiques et Applications: 78
Keywords: Mathematics , Applied mathematics , Engineering mathematics , Probabilities , Mathematics , Probability Theory and Stochastic Processes , Applications of Mathematics
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Call number:SPRINGER-2016-9783662496961:ONLINE Show nearby items on shelf
Title:Generated Dynamics of Markov and Quantum Processes
Author(s): Martin Janßen
Date:2016
Size:1 online resource (1 p.)
Note:10.1007/978-3-662-49696-1
Contents:Introduction - Dynamics of Relevant Variables- Generated Dynamics -- Formal Solutions -- Special Solutions -- Observables, States, Entropy and Generating Functionals -- Symmetries and Breaking of Symmetries -- Topology -- Selected
Applications
ISBN:9783662496961
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Physics , Economics, Mathematical , Engineering , Physics , Theoretical, Mathematical and Computational Physics , Engineering, general , Quantitative Finance
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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-2016-9783319310893:ONLINE Show nearby items on shelf
Title:Brownian Motion, Martingales, and Stochastic Calculus
Author(s): Jean-François Le Gall
Date:2016
Size:1 online resource (1 p.)
Note:10.1007/978-3-319-31089-3
Contents:Gaussian variables and Gaussian processes -- Brownian motion -- Filtrations and martingales -- Continuous semimartingales -- Stochastic integration -- General theory of Markov processes -- Brownian motion and partial differential equations -- Stoch astic differential equations -- Local times -- The monotone class lemma -- Discrete martingales -- References
ISBN:9783319310893
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Graduate Texts in Mathematics: 274
Keywords: Mathematics , Measure theory , Economics, Mathematical , System theory , Mathematical models , Probabilities , Mathematics , Probability Theory and Stochastic Processes , Quantitative Finance , Measure and Integration , Mathematical Modeling and Industrial Mathematics , Systems Theory, Control
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Call number:SPRINGER-2016-9783319301907:ONLINE Show nearby items on shelf
Title:Rabi N. Bhattacharya Selected Papers
Author(s):
Date:2016
Size:1 online resource (711 p.)
Note:10.1007/978-3-319-30190-7
Contents:Part I: Modes of Approximation -- Hall, Contributions of Rabi Bhattacharya to the Central Limit Theory and Normal Approximation -- Yoshida, Asymptotic Expansions for Stochastic Processes -- Shao, An Introduction to Normal Approximation -- Reprints - - Part II: Large Time Asymptotics for Markov Processes I: Diffusion -- Varadhan, Martingale Methods for the Central Limit Theorem -- Kurtz, Ergodicity and Central Limit Theorems for Markov Processes -- Reprints -- Part III: Large Time Asymptotics for Mark ov Processes II: Dynamical Systems and Iterated Maps -- Athreya, Dynamical Systems, IID Random Iterations, and Markov Chains -- Waymire, Random Dynamical Systems and Selected Works of Rabi Bhattacharya -- Reprints -- Part IV: Stochastic Foundations in App lied Sciences I: Economics -- Kamihigashi, Stachurski, Stability Analysis for Random Dynamical Systems in Economics -- Roy, Some Economic Applications of Recent Advances in Random Dynamical Systems -- Reprints -- Part V: Stochastic
Foundations in Applied Sciences II: Geophysics -- Thomann, Waymire, Advection-Dispersion in Fluid Media and Selected Works of Rabi Bhattacharya -- Flandoli, Romito, Cascade Representations for the Navier-Stokes Equations -- Reprints -- Part VI: Stoc hastic Foundations in Applied Sciences III: Statistics -- Dryden, Le, Preston, Wood, Nonparametric Statistical Methods on Manifolds -- Huckemann, Hotz, Nonparametric Statistics on Manifolds and Beyond -- Reprints
ISBN:9783319301907
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Mathematics , Probabilities , Statistics , Mathematics , Probability Theory and Stochastic Processes , Statistics for Business/Economics/Mathematical Finance/Insurance , Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Scien
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Call number:SPRINGER-2016-9783319072548:ONLINE Show nearby items on shelf
Title:Elements of Probability and Statistics An Introduction to Probability with de Finetti’s Approach and to Bayesian Statistics
Author(s): Francesca Biagini
Date:2016
Edition:1st ed. 2016
Size:1 online resource (27 p.)
Note:10.1007/978-3-319-07254-8
Contents:1 Random numbers -- 2 Discrete distributions -- 3 One-dimensional absolutely continuous distributions -- 4 Multi-dimensional absolutely continuous distributions -- 5 Convergence of distributions -- 6 Discrete time Markov chains -- 7 Continuous time Markov chains -- 8 Statistics -- 9 Combinatorics -- 10 Discrete distributions -- 11 One-dimensional absolutely continuous distributions -- 12 Absolutely continuous and multivariate distributions -- 13 Markov chains -- 14 Statistics -- 15 Elements of comb inatorics -- 16 Relations between discrete and absolutely continuous distributions -- 17 Some discrete distributions -- 18 Some one-dimensional absolutely continuous distributions -- 19 The normal distribution -- 20 Stirling's formula -- 21 Elements of an alysis -- 22 Bidimensional integrals
ISBN:9783319072548
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:UNITEXT: 98
Keywords: Mathematics , Business mathematics , Mathematical statistics , Probabilities , Physics , Statistics , Applied mathematics , Engineering mathematics , Mathematics , Probability Theory and Stochastic Processes , Statistical Theory and Methods , Probability and Statistics in Computer Science , Business Mathematics , Mathematical Methods in Physics , Appl.Mathematics/Computational Methods of Engineering
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Call number:SPRINGER-2014-9783662436967:ONLINE Show nearby items on shelf
Title:Semigroups, Boundary Value Problems and Markov Processes [electronic resource]
Author(s): Kazuaki Taira
Date:2014
Edition:2nd ed. 2014
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
Note:A careful and accessible exposition of functional analytic methods in stochastic analysis is provided in this book. It focuses on the interrelationship between three subjects in analysis: Markov processes, semi groups and ellipticboundary value probl ems. The author studies a general class of elliptic boundary value problems for second-order, Waldenfels integro-differential operators in partial differential equations and proves that this class of ellipticboundary value problems provides a general clas s of Feller semigroups in functional analysis. As an application, the author constructs a general class of Markov processes in probability in which a Markovian particle moves both by jumpsand continuously in the state space until it 'dies' at the time whe n it reaches the set where the particle is definitely absorbed. Augmenting the 1st edition published in 2004, this edition includes four new chapters and eightre-worked and expanded chapters. It is amply illustrated and all chapters are rounded off with N otes and Comments where bibliographical references are primarily discussed. Thanks to the kind feedback from many readers, some errors inthe first edition have been corrected. In order to keep the book up-to-date, new references have been added to the bib liography. Researchers and graduate students interested in PDEs, functional analysis and probability will find thisvolume useful
Contents:1.Introduction and Main Results
Part I Elements of Analysis
2.Elements of Probability Theory
3.Elements of Functional Analysis
4.Theory of Semigroups
Part II Elements of Partial Differential Equations
5.Theory of Distributions
6.Sobolev and Besov Spaces
7.Theory of Pseudo
Differential Operators
8.Waldenfels Operators and Maximum Principles
Part III Markov Processes, Semigroups and Boundary Value problems
9.Markov Processes, Transition Functions and Feller Semigroups
10.Feller Semigroups and Elliptic Boundary Value Problems
11.Proof of Theorem 1.3
12.Ma
ISBN:9783662436967
Series:eBooks
Series:SpringerLink
Series:Springer Monographs in Mathematics, 1439-7382
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Harmonic analysis , Functional analysis , Differential equations, partial , Distribution (Probability theory)
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Call number:SPRINGER-2014-9783642405235:ONLINE Show nearby items on shelf
Title:An Introduction to Markov Processes [electronic resource]
Author(s): Daniel W Stroock
Date:2014
Edition:2nd ed. 2014
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
Note:This book provides a rigorous but elementary introduction to the theory of Markov Processes on a countable state space. It should be accessible to students with a solid undergraduate background in mathematics, including studentsfrom engineering, econ omics, physics, and biology. Topics covered are: Doeblin's theory, general ergodic properties, and continuous time processes.Applications are dispersed throughout the book. In addition, a whole chapter isdevoted to reversible processes and the use of thei r associated Dirichlet forms to estimate the rate of convergence to equilibrium. These results are then applied to the analysis of the Metropolis (a.k.a simulated annealing) algorithm.The corrected and enlarged 2nd edition contains a new chapter in which the author develops computational methods for Markov chains on a finite state space. Most intriguing isthe section with a new technique for computing stationarymeasures, which is applied to derivations of Wilson's algorithm and Kirchoff's formula for span ning trees in a connected graph
Contents:Preface
Random Walks, a Good Place to Begin
Doeblin's Theory for Markov Chains
Stationary Probabilities
More about the Ergodic Theory of Markov Chains
Markov Processes in Continuous Time
Reversible Markov Processes
A minimal Introduction to Measure Theory
Notation
References
Index
ISBN:9783642405235
Series:eBooks
Series:SpringerLink
Series:Graduate Texts in Mathematics, 0072-5285 : v230
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Differentiable dynamical systems , Distribution (Probability theory)
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Call number:SPRINGER-2014-9783642376320:ONLINE Show nearby items on shelf
Title:Fluctuations of Lvy Processes with Applications [electronic resource] : Introductory Lectures
Author(s): Andreas E Kyprianou
Date:2014
Edition:2nd ed. 2014
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
Note:Lvy processes are the natural continuous-time analogue of random walks and form a rich class of stochastic processes around which a robust mathematical theory exists. Their application appears in the theory of many areas ofclassical and modern stocha stic processes including storage models, renewal processes, insurance risk models, optimal stopping problems, mathematical finance, continuous-state branching processes and positive self-similar Markovprocesses. This textbook is based on a series of gradu ate courses concerning the theory and application of Lvy processes from the perspective of their path fluctuations. Central to the presentation is the decomposition of paths interms of excursions from the running maximum as well as an understanding of sho rt- and long-term behaviour. The book aims to be mathematically rigorous while still providing an intuitive feel for underlying principles. The results andapplications often focus on the case of Lvy processes with jumps in only one direction, for which re cent theoretical advances have yielded a higher degree of mathematical tractability. The second edition additionally addresses recentdevelopments in the potential analysis of subordinators, Wiener-Hopf theory, the theory of scale functions and their appli cation to ruin theory, as well as including an extensive overview of the classical and modern theory of positiveself-similar Markov processes. Each chapter has a comprehensive set of exercises. Andreas Kyprianou has a degree in Mathematics from the Univer sity of Oxford and a Ph.D. in Probability Theory from The University of Sheffield. He iscurrently a Professor of Probability at the University of Bath, having held academic positions in Mathematics and Statistics Departments at the London School of Econom ics, Edinburgh University, Utrecht University and Heriot-WattUniversity, besides working for nearly two years as a research mathematician in the oil industry. His research is focused on pure and a
Contents:Lvy Processes and Applications
The LvyIt Decomposition and Path Structure
More Distributional and Path
Related Properties
General Storage Models and Paths of Bounded Variation
Subordinators at First Passage and Renewal Measures
The WienerHopf Factorisation
Lvy Processes at First Passage
Exit Problems for Spectrally Negative Processes
More on Scale Functions
Ruin Problems and Gerber
Shiu Theory
Applications to Optimal Stopping Problems
Continuous
State Branching Processes
Positive Self
similar Markov Processes
Epilogue
Hints for Exercises
ISBN:9783642376320
Series:eBooks
Series:SpringerLink
Series:Universitext, 0172-5939
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Finance , Distribution (Probability theory)
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Call number:SPRINGER-2014-9783319066745:ONLINE Show nearby items on shelf
Title:Input Modeling with Phase-Type Distributions and Markov Models [electronic resource] : Theory and Applications
Author(s): Peter Buchholz
Jan Kriege
Iryna Felko
Date:2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:Containing a summary of several recent results on Markov-based input modeling in a coherent notation, this book introduces and compares algorithms for parameter fitting and gives an overview of available software tools in thearea. Due to progress mad e in recent years with respect to new algorithms to generate PH distributions and Markovian arrival processes from measured data, the models outlined are useful alternatives to other distributions or stochasticprocesses used for input modeling. Graduate s tudents and researchers in applied probability, operations research and computer science along with practitioners using simulation or analytical models for performance analysis and capacityplanning will find the unified notation and up-to-date results pre sented useful. Input modeling is the key step in model based system analysis to adequately describe the load of a system using stochastic models. The goal of inputmodeling is to find a stochastic model to describe a sequence ofmeasurements from a real sys tem to model for example the inter-arrival times of packets in a computer network or failure times of components in a manufacturing plant.Typical application areas are performance and dependability analysis of computer systems, communication networks, log istics or manufacturing systems but also the analysis of biological or chemical reaction networks and similarproblems. Often the measured values have a high variability and are correlated. Its been known for a long time that Markov based models like phase type distributions or Markovian arrival processes are very general and allow one tocapture even complex behaviors. However, the parameterization of these models results often in a complex and non-linear optimization problem. Only recently, several new re sults about the modeling capabilities of Markov based models andalgorithms to fit the parameters of those models have been published
Contents:1. Introduction
2. Phase Type Distributions
3. Parameter Fitting for Phase Type Distributions
4. Markovian Arrival Processes
5. Parameter Fitting of MAPs
6. Stochastic Models including PH Distributions and MAPs
7. Software Tools
8. Conclusion
References
Index
ISBN:9783319066745
Series:eBooks
Series:SpringerLink
Series:SpringerBriefs in Mathematics, 2191-8198
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer software , Distribution (Probability theory)
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Call number:SPRINGER-2014-9783319057231:ONLINE Show nearby items on shelf
Title:Invariant Probabilities of Transition Functions [electronic resource]
Author(s): Radu Zaharopol
Date:2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:The structure of the set of all the invariant probabilities and the structure of various types of individual invariant probabilities of a transition function are two topics of significant interest in the theory of transitionfunctions, and are studied in this book. The results obtained are useful in ergodic theory and the theory of dynamical systems, which, in turn, can be applied in various other areas (like number theory). They are illustrated usingtransition functions defined by flows, semiflows, a nd one-parameter convolution semigroups of probability measures. In this book, all results on transition probabilities that have been published by the author between 2004 and 2008 areextended to transition functions. The proofs of the results obtained are new. For transition functions that satisfy very general conditions the book describes an ergodic decomposition that provides relevant information on the structureof the corresponding set of invariant probabilities. Ergodic decomposition means a splitting of the state space, where the invariant ergodic probability measures play a significant role. Other topics covered include: characterizationsof the supports of various types of invariant probability measures and the use of these to obtain criteria for un ique ergodicity, and the proofs of two mean ergodic theorems for a certain type of transition functions. The book will beof interest to mathematicians working in ergodic theory, dynamical systems, or the theory of Markov processes. Biologists, physicists and economists interested in interacting particle systems and rigorous mathematics will also findthis book a valuable resource. Parts of it are suitable for advanced graduate courses. Prerequisites are basic notions and results on functional analysis, gen eral topology, measure theory, the Bochner integral and some of itsapplications
Contents:Introduction
1.Transition Probabilities
2.Transition Functions
3.Vector Integrals and A.E. Convergence
4.Special Topics
5.The KBBY Ergodic Decomposition, Part I
6.The KBBY Ergodic Decomposition, Part II
7.Feller Transition Functions
Appendices: A.Semiflows and Flows: Introduction
B.Measures and Convolutions
Bibliography
Index
ISBN:9783319057231
Series:eBooks
Series:SpringerLink
Series:Probability and Its Applications, 1431-7028
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Differentiable dynamical systems , Operator theory , Potential theory (Mathematics) , Distribution (Probability theory)
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Call number:SPRINGER-2014-9783319057149:ONLINE Show nearby items on shelf
Title:Stochastic Differential Equations, Backward SDEs, Partial Differential Equations [electronic resource]
Author(s): Etienne Pardoux
Aurel Rcanu
Date:2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:This research monograph presents results to researchers in stochastic calculus, forward and backward stochastic differential equations, connections between diffusion processes and second order partial differential equations(PDEs), and financial mathe matics. It pays special attention to the relations between SDEs/BSDEs and second order PDEs under minimal regularity assumptions, and also extends those results to equations with multivalued coefficients. Theauthors present in particular the theory of ref lected SDEs in the above mentioned framework and include exercises at the end of each chapter. Stochastic calculus and stochastic differential equations (SDEs) were first introduced by K.It in the 1940s, in order to construct the path of diffusion process es (which are continuous time Markov processes with continuous trajectories taking their values in a finite dimensional vector space or manifold), which had beenstudied from a more analytic point of view by Kolmogorov in the 1930s. Since then, this topic has become an important subject of Mathematics and Applied Mathematics, because of its mathematical richness and its importance forapplications in many areas of Physics, Biology, Economics and Finance, where random processes play an increasingly important role. One important aspect is the connection between diffusion processes and linear partial differentialequations of second order, which is in particular the basis for Monte Carlo numerical methods for linear PDEs. Since the pioneering work of Peng and P ardoux in the early 1990s, a new type of SDEs called backward stochastic differentialequations (BSDEs) has emerged. The two main reasons why this new class of equations is important are the connection between BSDEs and semilinear PDEs, and the fact that B SDEs constitute a natural generalization of the famous Black andScholes model from Mathematical Finance, and thus offer a natural mathematical framework for the formulation of many new models in Finan
Contents:Introduction
Background of Stochastic Analysis
Itos Stochastic Calculus
Stochastic Differential Equations
SDE with Multivalued Drift
Backward SDE
Annexes
Bibliography
Index
ISBN:9783319057149
Series:eBooks
Series:SpringerLink
Series:Stochastic Modelling and Applied Probability, 0172-4568 : v69
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Differential equations, partial , Distribution (Probability theory)
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Call number:SPRINGER-2014-9783319031521:ONLINE Show nearby items on shelf
Title:Random Walks on Disordered Media and their Scaling Limits [electronic resource] : cole d't de Probabilits de Saint-Flour XL - 2010
Author(s): Takashi Kumagai
Date:2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:In these lecture notes, we will analyze the behavior of random walk on disordered mediaby means ofboth probabilistic and analytic methods, and will study the scalinglimits. We will focus on the discrete potential theory andhow the theory is effective ly used in the analysis of disordered media.Thefirst few chapters of the notes can be used as an introduction to discrete potential theory. Recently, there has beensignificantprogress onthetheoryof random walkon disordered media such as fractals and rand om media.Random walk on a percolation cluster(the ant in the labyrinth)is one of the typical examples. In 1986, H. Kesten showedtheanomalousbehavior of a random walk on a percolation cluster at critical probability. Partly motivated by this work, analysis and diffusion processes on fractals have been developed since the late eighties. As a result, various new methods havebeen produced to estimate heat kernels on disordered media. These developments are summarized in the notes
Contents:Introduction
Weighted graphs and the associated Markov chains
Heat kernel estimates General theory
Heat kernel estimates using effective resistance
Heat kernel estimates for random weighted graphs
Alexander
Orbach conjecture holds when two
point functions behave nicely
Further results for random walk on IIC
Random conductance model
ISBN:9783319031521
Series:eBooks
Series:SpringerLink
Series:Lecture Notes in Mathematics, 0075-8434 : v2101
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Potential theory (Mathematics) , Distribution (Probability theory)
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Call number:SPRINGER-2014-9783319024356:ONLINE Show nearby items on shelf
Title:Basic Concepts in Computational Physics [electronic resource]
Author(s): Benjamin A. Stickler
Ewald Schachinger
Date:2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:With the development of ever more powerful computers a new branch of physics and engineering evolved over the last few decades: Computer Simulation or Computational Physics. It serves two main purposes: - Solution of complexmathematical problems such as, differential equations, minimization/optimization, or high-dimensional sums/integrals. - Direct simulation of physical processes, as for instance, molecular dynamics or Monte-Carlo simulation ofphysical/chemical/technical processes. Consequently, the book is divided into two main parts: Deterministic methods and stochastic methods. Based on concrete problems, the first part discusses numerical differentiation and integration,and the treatment of ordinary differential equations. This is augmented by n otes on the numerics of partial differential equations. The second part discusses the generation of random numbers, summarizes the basics of stochastics whichis then followed by the introduction of various Monte-Carlo (MC) methods. Specific emphasis is on MARKOV chain MC algorithms. All this is again augmented by numerous applications from physics. The final two chapters on Data Analysisand Stochastic Optimization share the two main topics as a common denominator. The book offers a number of appendices to provide the reader with more detailed information on various topics discussed in the main part. Nevertheless, thereader should be familiar with the most important concepts of statistics and probability theory albeit two appendices have been dedicated to provide a rudimentary discussion
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 SCHRDINGER Equation
Numerics of Partial Differential Equations
Part II Stochastic Methods
Pseudo Random Number Generators
Random Sampling Methods
A Brief Introduction to Monte
Carlo Methods
The
ISBN:9783319024356
Series:eBooks
Series:SpringerLink
Series:Physics and Astronomy (Springer-11651)
Keywords: Chemistry , Computer science Mathematics , Engineering mathematics
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Call number:SPRINGER-2014-9781461491613:ONLINE Show nearby items on shelf
Title:Nonlinear Maps and their Applications [electronic resource] : Selected Contributions from the NOMA 2011 International Workshop
Author(s): Clara Grcio
Daniele Fournier-Prunaret
Tetsushi Ueta
Yoshifumi Nishio
Date:2014
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:In the field of Dynamical Systems, nonlinear iterative processes play an important role. Nonlinear mappings can be found as immediate models for many systems from different scientific areas, such as engineering, economics,biology, or can also be obta ined via numerical methods permitting to solve non-linear differential equations. In both cases, the understanding of specific dynamical behaviors and phenomena is of the greatest interest for scientists.This volume contains papers that were presented at the International Workshop on Nonlinear Maps and their Applications (NOMA 2011) held in vora, Portugal, on September 15-16, 2011. This kind of collaborative effort is of paramountimportance in promoting communication among the various groups that work in dynamical systems and networks in their research theoretical studies as well as for applications. This volume is suitable for graduate students as well asresearchers in the field
Contents:J. P. Almeida A. A. Pinto D. A. Rand, Renormalization of circlediffeomorphism sequences and Markov sequences
F. Balibrea M. V. Caballero, Examples of Lyapunov exponents in two dimensional systems
R. A. da Costa S. N. Dorogovtsev A.V. Goltsev J. F. F. Mendes, Characteristics of the explosive percolation transition
E. S. Roberts A. Annibale A. C. C. Coolen, Controlled Markovian dynamics of graphs: unbiased generation of random graphs with prescribed topological properties
G. Bettencourt, A case leading to rationalist of the drift
L. S. Efremova, Remarks on the nonwanderi
ISBN:9781461491613
Series:eBooks
Series:SpringerLink
Series:Springer Proceedings in Mathematics & Statistics, 2194-1009 : v57
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Differentiable dynamical systems
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Call number:SPRINGER-2014-9781447153610:ONLINE Show nearby items on shelf
Title:Probability Theory [electronic resource] : A Comprehensive Course
Author(s): Achim Klenke
Date:2014
Edition:2nd ed. 2014
Publisher:London : Springer London : Imprint: Springer
Size:1 online resource
Note:This second edition of the popular textbook contains a comprehensive course in modern probability theory. Overall, probabilistic concepts play an increasingly important role in mathematics, physics, biology, financial engineeringand computer science. They help us in understanding magnetism, amorphous media, genetic diversity and the perils of random developments at financial markets, and they guide us in constructing more efficient algorithms. To addressthese concepts, the title covers a wide variet y of topics, many of which are not usually found in introductory textbooks, such as: limit theorems for sums of random variables martingales percolation Markov chains andelectrical networks construction of stochastic processes Poisson point process and infinite divisibility large deviation principles and statistical physics Brownian motion stochastic integral and stochasticdifferential equations. The theory is developed rigorously and in a self-contained way, with the chapters on measure theory interlaced with the probabilistic chapters in order to display the power of the abstract concepts inprobability theory. This second edition has been carefully extended and includes many new features. It contains updated figures (over 50), computer simulat ions and some difficult proofs have been made more accessible. A wealth ofexamples and more than 270 exercises as well as biographic details of key mathematicians support and enliven the presentation. It will be of use to students and researchers in mathe matics and statistics in physics, computer science,economics and biology
Contents:Basic Measure Theory
Independence
Generating Functions
The Integral
Moments and Laws of Large Numbers
Convergence Theorems
Lp
Spaces and the RadonNikodym Theorem
Conditional Expectations
Martingales
Optional Sampling Theorems
Martingale Convergence Theorems and Their Applications
Backwards Martingales and Exchangeability
Convergence of Measures
Probability Measures on Product Spaces
Characteristic Functions and the Central Limit Theorem
Infinitely Divisible Distributions
Markov Chains
Convergence of Markov Chains
Markov Chains and Electr
ISBN:9781447153610
Series:eBooks
Series:SpringerLink
Series:Universitext, 0172-5939
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Differentiable dynamical systems , Functional analysis , Distribution (Probability theory)
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Call number:SPRINGER-2013-9788132207634:ONLINE Show nearby items on shelf
Title:Statistical Inference for Discrete Time Stochastic Processes [electronic resource]
Author(s): M. B Rajarshi
Date:2013
Publisher:India : Springer India : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This work is an overview of statistical inference in stationary, discrete time stochastic processes. Results in the last fifteen years, particularly on non-Gaussian sequences and semi-parametric and non-parametric analysis havebeen reviewed. The firs t chapter gives a background of results on martingales and strong mixing sequences, which enable us to generate various classes of CAN estimators in the case of dependent observations. Topics discussed includeinference in Markov chains and extension of Ma rkov chains such as Raftery's Mixture Transition Density model and Hidden Markov chains and extensions of ARMA models with a Binomial, Poisson, Geometric, Exponential, Gamma, Weibull,Lognormal, Inverse Gaussian and Cauchy as stationary distributions. It f urther discusses applications of semi-parametric methods of estimation such as conditional least squares and estimating functions in stochastic models.Construction of confidence intervals based on estimating functions is discussed in some detail. Kernel b ased estimation of joint density and conditional expectation are also discussed. Bootstrap and other resampling procedures fordependent sequences such as Markov chains, Markov sequences, linear auto-regressive moving average sequences, block based bootstr ap for stationary sequences and other block based procedures are also discussed in some detail. This workcan be useful for researchers interested in knowing developments in inference in discrete time stochastic processes. It can be used as a material for advanced level research students
Note:Springer eBooks
Contents:CAN Estimators from dependent observations
Markov chains and their extensions
Non
Gaussian ARMA models
Estimating Functions
Estimation of joint densities and conditional expectation
Bootstrap and other resampling procedures
Index
ISBN:9788132207634
Series:e-books
Series:SpringerLink (Online service)
Series:SpringerBriefs in Statistics, 2191-544X
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics
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Call number:SPRINGER-2013-9783642393631:ONLINE Show nearby items on shelf
Title:Stochastic Simulation and Monte Carlo Methods [electronic resource] : Mathematical Foundations of Stochastic Simulation
Author(s): Carl Graham
Denis Talay
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:In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners aim to simulate more and more complex systems, and thus userandom parameters as wel l as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a highly complex mathematical undertaking.Approaching these issues, the authors present stochas tic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As a result, the bookis a self-contained and rigorous study of the numerical methods within a th eoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingaletheory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochasti c differential equations. In particular, they review the essential properties of It integrals and prove fundamental results on theprobabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing st ochastic numerical methods, both from an algorithmic and theoretical point of view. The book combinesadvanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes. It isintended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professional s working with stochastic simulations, who willbenefit from the ability to reliably estimate and control the accuracy of their simulations.
Note:Springer eBooks
Contents:Part I:Principles of Monte Carlo Methods
1.Introduction
2.Strong Law of Large Numbers and Monte Carlo Methods
3.Non Asymptotic Error Estimates for Monte Carlo Methods
Part II:Exact and Approximate Simulation of Markov Processes
4.Poisson Processes
5.Discrete
Space Markov Processes
6.Continuous
Space Markov Processes with Jumps
7.Discretization of Stochastic Differential Equations
Part III:Variance Reduction, Girsanovs Theorem, and Stochastic Algorithms
8.Variance Reduction and Stochastic Differential Equations
9.Stochastic Algorithms
References
Index
ISBN:9783642393631
Series:e-books
Series:SpringerLink (Online service)
Series:Stochastic Modelling and Applied Probability, 0172-4568 : v68
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Finance , Numerical analysis , Distribution (Probability theory)
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Call number:SPRINGER-2013-9783642349041:ONLINE Show nearby items on shelf
Title:Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications [electronic resource]
Author(s): Joo Lita da Silva
Frederico Caeiro
Isabel Natrio
Carlos A Braumann
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 of the Selected Papers from Portugal is a product of the Seventeenth Congress of the Portuguese Statistical Society, held at the beautiful resort seaside city of Sesimbra, Portugal, from September 30 to October 3,2009. It covers a broad s cope of theoretical, methodological as well as application-oriented articles in domains such as: Linear Models and Regression, Survival Analysis, Extreme Value Theory, Statistics of Diffusions, Markov Processesand other Statistical Applications
Note:Springer eBooks
Contents:Part I Invited Sessions: Youden Square with Split Units (Stanisaw Franciszek Mejza and Shinji Kuriki)
Likelihood and PLS Estimators for Structural Equation Modeling: an Assessment of Sample Size, Skewness and Model Misspecification Effects (Manuel J. Vilares and Pedro S. Coelho)
Part II Communications: A Parametric Cure Model with Covariates (Ana M. Abreu and Cristina S. Rocha)
Survival Analysis Applied to the Study of Time from Diagnosis of HIV
1 Infection to AIDS in Portugal (Marta Alves, Cristina S. Rocha and Maria Teresa Paixo)
A new Independence Test for VaR Violations (P
ISBN:9783642349041
Series:e-books
Series:SpringerLink (Online service)
Series:Studies in Theoretical and Applied Statistics
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics
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Call number:SPRINGER-2013-9783642331312:ONLINE Show nearby items on shelf
Title:Quasi-Stationary Distributions [electronic resource] : Markov Chains, Diffusions and Dynamical Systems
Author(s): Pierre Collet
Servet Martnez
Jaime San Martn
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:Main concepts of quasi-stationary distributions (QSDs) for killed processes are the focus of the present volume. For diffusions, the killing is at the boundary and for dynamical systems there is a trap. The authors present theQSDs as the ones that al low describing the long-term behavior conditioned to not being killed. Studies in this research area started with Kolmogorov and Yaglom and in the last few decades have received a great deal of attention. Theauthors provide the exponential distribution pr operty of the killing time for QSDs, present the more general result on their existence and study the process of trajectories that survive forever. For birth-and-death chains anddiffusions, the existence of a single or a continuum of QSDs is described. Th ey study the convergence to the extremal QSD and give the classification of the survival process. In this monograph, the authors discuss Gibbs QSDs forsymbolic systems and absolutely continuous QSDs for repellers. The findings described are relevant to re searchers in the fields of Markov chains, diffusions, potential theory, dynamical systems, and in areas where extinction is acentral concept. The theory is illustrated with numerous examples. The volume uniquely presents the distribution behavior of indiv iduals who survive in a decaying population for a very long time. It also provides the background forapplications in mathematical ecology, statistical physics, computer sciences, and economics
Note:Springer eBooks
Contents:1.Introduction
2.Quasi
stationary Distributions: General Results
3.Markov Chains on Finite Spaces
4.Markov Chains on Countable Spaces
5.Birth and Death Chains
6.Regular Diffusions on [0,)
7.Infinity as Entrance Boundary
8.Dynamical Systems
References
Index
Table of Notations
Citations Index.
ISBN:9783642331312
Series:e-books
Series:SpringerLink (Online service)
Series:Probability and Its Applications, 1431-7028
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Differentiable dynamical systems , Differential equations, partial , Genetics Mathematics , Distribution (Probability theory)
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Call number:SPRINGER-2013-9783642318986:ONLINE Show nearby items on shelf
Title:Mouvement brownien, martingales et calcul stochastique [electronic resource]
Author(s): Jean-Francois Le Gall
Date:2013
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
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Note:Cet ouvrage propose une approche concise mais complte de la thorie de l'intgrale stochastique dans le cadre gnral des semimartingales continues. Aprs une introduction au mouvement brownien et ses principalesproprits, les martingales et les semimarti ngales continues sont prsentes en dtail avant la construction de l'intgrale stochastique. Les outils du calcul stochastique, incluant la formule d'It, le thorme d'arrt et denombreuses applications, sont traits de manire rigoureuse. Le livre contient aussi un chapitre sur les processus de Markov et un autre sur les quations diffrentielles stochastiques, avec une preuve dtaille des propritsmarkoviennes des solutions. De nombreux exercices permettent au lecteur de se familiariser avec les techniques du calcu l stochastique. This book offers a rigorous and self-contained approach to the theory of stochastic integration andstochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including It's formul a, the optional stopping theorem and the Girsanov theorem are treated in detail includingmany important applications. Two chapters are devoted to general Markov processes and to stochastic differential equations, with a complete derivation of Markovian pr operties of solutions in the Lipschitz case. Numerous exercises helpthe reader to get acquainted with the techniques of stochastic calculus
Note:Springer eBooks
ISBN:9783642318986
Series:e-books
Series:SpringerLink (Online service)
Series:Mathmatiques et Applications, 1154-483X : v71
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Distribution (Probability theory)
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Call number:SPRINGER-2013-9783642302534:ONLINE Show nearby items on shelf
Title:Bayesian Hierarchical Space-Time Models with Application to Significant Wave Height [electronic resource]
Author(s): Erik Vanem
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 book provides an example of a thorough statistical treatment in space and time of ocean wave data. It is demonstrated how the flexible framework of Bayesian hierarchical space-time models can be applied to oceanographicprocesses such as signific ant wave height in order to describe dependence structures and uncertainties in the data. This monograph is a research book and it is in some sense cross-disciplinary. The methodology itself is firmly rootedin the statistical research tradition, based on probability theory and stochastic processes. However, the methodology has been applied to a problem within physical oceanography, analysing data for significant wave height, which are ofcrucial importance to ocean engineering disciplines. Indeed, the stat istical properties of significant wave height are important for the design, construction and operation of ships and other marine and coastal structures. Furthermore,the book addresses the question of whether climate change has an effect of the ocean wave climate, and if so what these effects might be. Thus, this book is an important contribution to the on-going debate on climate change, itsimplications and how to adapt to a changing climate, with a particular focus on the maritime industries and the marin e environment. This book should be of general interest to anyone with an interest in statistical modelling ofenvironmental processes, and in particular to those with a particular interest in the ocean wave climate. It is written on a level that should be understandable to everyone with a basic background in statistics or elementarymathematics, and an introduction to some basic concepts is given in appendices for the uninitiated reader. The intended readership incudes students and professionals involved in statistics, oceanography, ocean engineering,environmental research, climate sciences and risk assessment. Moreover, different stakeholders within the maritime industries such as design offices, classif
Note:Springer eBooks
Contents:Preface
Acronyms
1.Introduction and Background
2.Literature Survey on StochasticWave Models
3.A Bayesian Hierarchical Space
Time Model for Significant Wave Height
4.Including a Log
Transform of the Data
6.Bayesian Hierarchical Modelling of the Ocean Windiness
7.Application: Impacts on Ship Structural Loads
8.Case study: Modelling the Effect of Climate Change on the Worlds Oceans
9.Summary and Conclusions
A.Markov Chain Monte Carlo Methods
B.Extreme Value Modelling
C.Markov Random Fields
D.Derivation of the Full Conditionals of the Bayesian Hierarchical
ISBN:9783642302534
Series:e-books
Series:SpringerLink (Online service)
Series:Ocean Engineering & Oceanography, 2194-6396 : v2
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Distribution (Probability theory)
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Call number:SPRINGER-2013-9783642259692:ONLINE Show nearby items on shelf
Title:Inference for Diffusion Processes [electronic resource] : With Applications in Life Sciences
Author(s): Christiane Fuchs
Date:2013
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
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Note:Diffusion processes are a promising instrument for realistically modelling the time-continuous evolution of phenomena not only in the natural sciences but also in finance and economics. Their mathematical theory, however, ischallenging, and hence dif fusion modelling is often carried out incorrectly, and the according statistical inference is considered almost exclusively by theoreticians. This book explains both topics in an illustrative way which alsoaddresses practitioners. It provides a complete o verview of the current state of research and presents important, novel insights. The theory is demonstrated using real data applications
Note:Springer eBooks
Contents:Introduction
Stochastic Modelling in Life Sciences
Stochastic Differential Equations and Diffusions in a Nutshell
Approximation of Markov Jump Processes by Diffusions
Diffusion Models in Life Sciences
Parametric Inference for Discretely
observed Diffusions
Bayesian Inference for Diffusions with Low
frequency Observations
Application I: Spread of Influenza
Application II: Analysis of Molecular Binding
Conclusion and Outlook
Benchmark Models
Miscellaneous
Supplementary Material for Application I
Supplementary Material for Application II
Notation
Refer
ISBN:9783642259692
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Statistical methods , Mathematical statistics , Economics Statistics
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Call number:SPRINGER-2013-9783319003214:ONLINE Show nearby items on shelf
Title:Sminaire de Probabilits XLV [electronic resource]
Author(s): Catherine Donati-Martin
Antoine Lejay
Alain Rouault
Date:2013
Publisher:Heidelberg : Springer International Publishing : Imprint: Springer
Size:1 online resource
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Note:The series of advanced courses initiated in Sminaire de Probabilits XXXIII continues with a course by Ivan Nourdin on Gaussian approximations using Malliavin calculus. The Sminaire also occasionally publishes a series ofcontributions on a unifying su bject in this spirit, selected participants to the September 2011 Conference on Stochastic Filtrations, held in Strasbourg and organized by Michel mery, have also contributed to the present volume. Therest of the work covers a wide range of topics, such a s stochastic calculus and Markov processes, random matrices and free probability, and combinatorial optimization
Note:Springer eBooks
Contents:Special Course: I. Nourdin: Lectures on Gaussian approximations with Malliavin calculus
Other Contributions: V. Prokaj: Some sufficient conditions for the ergodicity of the Lvy
transformation
S. Laurent: Vershiks intermediate level standardness criterion and the scale of an automorphism
C. Dellacherie and M.mery: Filtrations indexed by ordinals application to a conjecture of S. Laurent
M. mery: A planar Borel set which divides every Borel product
J. Brossard et C. Leuridan: Characterising Ocone local martingales with reflections
H. Hashimoto: Approximation and sta
ISBN:9783319003214
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Mathematics, 0075-8434 : v2078
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Distribution (Probability theory)
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Call number:SPRINGER-2013-9781461486633:ONLINE Show nearby items on shelf
Title:Mathematical Methods in Robust Control of Linear Stochastic Systems [electronic resource]
Author(s): Vasile Dragan
Toader Morozan
Adrian-Mihail Stoica
Date:2013
Edition:2nd ed. 2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
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Note:This second edition of Mathematical Methods in the Robust Control of Linear Stochastic Systems includes a large number of recent results in the control of linear stochastic systems. More specifically, the new results presentedare: - A unified and abs tract framework for Riccati type equations arising in the stochastic control - Stability and control problems for systems perturbed by homogeneous Markov processes with infinite number of states - MixedH2 /Hcontrol problem and numerical procedures - Linea r differential equations with positive evolution on ordered Banach spaces with applications for stochastic systems including both multiplicative white noise and Markovian jumpsrepresented by a Markov chain with countable infinite set of states - Kalman fi ltering for stochastic systems subject both to state dependent noise and Markovian jumps - Hreduced order filters for stochastic systems The bookwill appeal to graduate students, researchers in advanced control engineering, finance, mathematical systems t heory, applied probability and stochastic processes, and numerical analysis. From Reviews of the First Edition: This bookis concerned with robust control of stochastic systems. One of the main features is its coverage of jump Markovian systems. Overall, this book presents results taking into consideration both white noise and Markov chainperturbations. It is clearly written and should be useful for people working in applied mathematics and in control and systems theory. The references cited provide furth er reading sources. (George Yin, Mathematical Reviews, Issue2007 m) This book considers linear time varying stochastic systems, subjected to white noise disturbances and system parameter Markovian jumping, in the context of optimal control robust stabili zation, and disturbance attenuation. The material presented in the book is organized in seven chapters. The book is very well written and organized. is a valuabl
Note:Springer eBooks
Contents:Preliminariesto Probability Theory and Stochastic Differential Equations
Linear Differential Equations with Positive Evolution on Ordered Banach Spaces
Exponential Stability in Mean Square
Structural Properties of Linear Stochastic Systems
A Class of Nonlinear Differential Equations on an Ordered Linear Space of Symmetric Matrices with Applications to Riccati Differential Equations of Stochastic Control
Linear Quadratic Optimization Problems for Linear Stochastic Systems
Stochastic H2 Optimal Control
Stochastic Version of the Bounded Real Lemma and Applications
Robust
ISBN:9781461486633
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Systems theory , Distribution (Probability theory)
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Call number:SPRINGER-2013-9781461477891:ONLINE Show nearby items on shelf
Title:State-Space Models [electronic resource] : Applications in Economics and Finance
Author(s): Yong Zeng
Shu Wu
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
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Note:State-space models as an important mathematical tool has been widely used in many different fields. This edited collection explores recent theoretical developments of the models and their applications in economics and finance. Thebook includes nonlin ear andnon-Gaussian time series models, regime-switching and hidden Markov models, continuous- or discrete-time state processes, and models of equally-spaced or irregularly-spaced (discrete or continuous)observations.The contributed chapters are divided i nto four parts. The first part is on Particle Filtering and Parameter Learning in Nonlinear State-Space Models.The second part focuseson the application of Linear State-SpaceModels in Macroeconomics and Finance.The third part deals with Hidden Markov Mode ls, Regime Switching and Mathematical Finance and the fourth part is on Nonlinear State-Space Models for High Frequency Financial Data. The book willappeal to graduate students and researchers studying state-space modeling in economics, statistics, and ma thematics, as well as to finance professionals. Yong Zeng is a professor in Department of Mathematics and Statistics atUniversity of Missouri at Kansas City. His main research interest includes mathematical finance, financial econometrics, stochastic nonl inear filtering, and Bayesian statistical analysis. Notably, he developed the statistical analysisvia filtering for financial ultra-high frequency data, where the model can be viewed as a random-arrival-time state space model. He has published in Mathemat ical Finance, International Journal of Theoretical and Applied Finance,Applied Mathematical Finance, IEEE Transactions on Automatic Control, Statistical Inference for Stochastic Processes, among others. He held visiting associate professor positions at Pr inceton University and the University of Tennessee.He received his B.S. from Fudan University in 1990, M.S. from University of Georgia in 1994, and Ph.D. from University of Wisconsin at Ma
Note:Springer eBooks
Contents:Particle Filtering and Parameter Learning in Nonlinear State
Space Models
Linear State
Space Models in Macroeconomics and Finance
Hidden Markov Models, Regime
Switching, and Mathematical Finance
Nonlinear State
Space Models for High Frequency Financial Data
Index
ISBN:9781461477891
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics and Econometrics for Finance : v1
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics , Economics Statistics
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Call number:SPRINGER-2013-9781461469834:ONLINE Show nearby items on shelf
Title:Continuous Average Control of Piecewise Deterministic Markov Processes [electronic resource]
Author(s): Oswaldo Luiz do Valle Costa
Francois Dufour
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
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Note:The intent of this book is to present recent results in the control theory for the long run average continuous control problem of piecewise deterministic Markov processes (PDMPs). The book focuses mainly on the long run averagecost criteria and exten ds to the PDMPs some well-known techniques related to discrete-time and continuous-time Markov decision processes, including the so-called ``average inequality approach'', ``vanishing discount technique'' and``policy iteration algorithm''. We believe that what is unique about our approach is that, by using the special features of the PDMPs, we trace a parallel with the general theory for discrete-time Markov Decision Processes rather thanthe continuous-time case. The two main reasons for doing that is to use the powerful tools developed in the discrete-time framework and to avoid working with the infinitesimal generator associated to a PDMP, which in most cases has itsdomain of definition difficult to be characterized. Although the book is mainly intended to be a theoretically oriented text, it also contains some motivational examples. The book is targeted primarily for advanced students andpractitioners of control theory. The book will be a valuable source for experts in the field of Markov decision proc esses. Moreover, the book should be suitable for certain advanced courses or seminars. As background, one needs anacquaintance with the theory of Markov decision processes and some knowledge of stochastic processes and modern analysis.
Note:Springer eBooks
ISBN:9781461469834
Series:e-books
Series:SpringerLink (Online service)
Series:SpringerBriefs in Mathematics, 2191-8198
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Systems theory , Distribution (Probability theory)
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Call number:SPRINGER-2013-9781461469803:ONLINE Show nearby items on shelf
Title:Stochastic Tools in Mathematics and Science [electronic resource]
Author(s): Alexandre J Chorin
Ole H Hald
Date:2013
Edition:3rd ed. 2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
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Note:Stochastic Tools in Mathematics and Science covers basic stochastic tools used in physics, chemistry, engineering and the life sciences. The topics covered include conditional expectations, stochastic processes, Brownianmotion and its relation to par tial differential equations, Langevin equations, the Liouville and Fokker-Planck equations, as well as Markov chain Monte Carlo algorithms, renormalization, basic statistical mechanics, and generalizedLangevin equations and the Mori-Zwanzig formalism. The applications include sampling algorithms, data assimilation, prediction from partial data, spectral analysis, and turbulence. The book is based on lecture notes from a classthat has attracted graduate and advanced undergraduate students from mathematics and from many other science departments at the University of California, Berkeley. Each chapter is followed by exercises. The book will be useful forscientists and engineers working in a wide range of fields and applications. For this new edition the ma terial has been thoroughly reorganized and updated, and new sections on scaling, sampling, filtering and data assimilation,based on recent research, have been added. There are additional figures and exercises. Review of earlier edition: This is an excel lent concise textbook which can be used for self-study by graduate and advanced undergraduatestudents and as a recommended textbook for an introductory course on probabilistic tools in science. Mathematical Reviews, 2006
Note:Springer eBooks
Contents:Preliminary
Probability
Brownian Motion
Stationary Stochastic Processes
Statistical Mechanics
Index
Time
Dependent Statistical Mechanics
ISBN:9781461469803
Series:e-books
Series:SpringerLink (Online service)
Series:Texts in Applied Mathematics, 0939-2475 : v58
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Distribution (Probability theory) , Hydraulic engineering
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Call number:SPRINGER-2013-9781461462408:ONLINE Show nearby items on shelf
Title:Advances in Superprocesses and Nonlinear PDEs [electronic resource]
Author(s): Janos Englander
Brian Rider
Date:2013
Publisher:Boston, MA : Springer US : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Sergei Kuznetsov is one of the top experts on measure valued branching processes (also known as superprocesses) and their connection to nonlinear partial dierential operators. His research interests range from stochasticprocesses and partial dierenti al equations to mathematical statistics, time series analysis and statistical software he has over 90 papers published in international research journals. His most well known contribution toprobability theory is the Kuznetsov-measure. A conference honori ng his 60thbirthday has been organized at Boulder, Colorado in the summer of 2010, with the participation of Sergei Kuznetsovs mentor and major co-author,Eugene Dynkin. The conference focused on topics related to superprocesses, branching diffusions and n onlinear partial differential equations. In particular, connections to the so-called Kuznetsov-measure were emphasized. Leading experts in the field as well as young researchers contributed to the conference. The meeting was organized by J. Englander and B. Rider (U. of Colorado).
Note:Springer eBooks
Contents:Markov processes and their applications to partial differential equationsKuznetsov's contributions
Stochastic equations on projective systems of groups
Modeling competition between two influenza strains
Asymptotic Results for Near Critical Bienaym\'e
Galton
Watson and Catalyst
Reactant Branching Processes
Some path large deviation results for a branching diffusion
Longtime Behavior for Mutually Catalytic Branching
Super
Brownian motion: Lp
convergence of martingales through the pathwise spine decomposition
ISBN:9781461462408
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Proceedings in Mathematics & Statistics, 2194-1009 : v38
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Differential equations, partial , Distribution (Probability theory) , Economics Statistics
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Call number:SPRINGER-2013-9781461453178:ONLINE Show nearby items on shelf
Title:Introduction to Queueing Systems with Telecommunication Applications [electronic resource]
Author(s): Laszlo Lakatos
Laszlo Szeidl
Miklos Telek
Date:2013
Publisher:Boston, MA : Springer US : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The book is composed of two main parts: mathematical background and queueing systems with applications. The mathematical background is a self containing introduction to the stochastic processes of the later studies queueingsystems. It starts with a q uick introduction to probability theory and stochastic processes and continues with chapters on Markov chains and regenerative processes. More recent advances of queueing systems are based on phase typedistributions, Markov arrival processes and quasy bir th death processes, which are introduced in the last chapter of the first part. The second part is devoted to queueing models and their applications. After the introduction of thebasic Markovian (from M/M/1 to M/M/1//N) and non-Markovian (M/G/1, G/M/1) qu eueing systems, a chapter presents the analysis of queues with phase type distributions, Markov arrival processes (from PH/M/1 to MAP/PH/1/K). The nextchapter presents the classical queueing network results and the rest of this part is devoted to the appl ication examples. There are queueing models for bandwidth charing with different traffic classes, slotted multiplexers, ATMswitches, media access protocols like Aloha and IEEE 802.11b, priority systems and retrial systems. An appendix supplements the tech nical content with Laplace and z transformation rules, Bessel functions and a list of notations. Thebook contains examples and exercises throughout and could be used for graduate students in engineering, mathematics and sciences
Note:Springer eBooks
Contents:Preface
Introduction to probability theory
Introduction to stochastic processes
Markov chains
Renewal and regenerative processes
Markov chains with special structures
Introduction to queueing systems
Markovian queueing systems
Non
Markovian queueing systems
Queueing systems with structured Markov chains
Queueing networks
Applied queueing systems
Functions and transforms
Exercises
References
ISBN:9781461453178
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer system performance , Distribution (Probability theory) , Telecommunication
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Call number:SPRINGER-2013-9781461446453:ONLINE Show nearby items on shelf
Title:Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies [electronic resource]
Author(s): Eliane Regina Rodrigues
Jorge Alberto Achcar
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
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Note:Springer 2013 e-book collections
Note:In this brief we consider some stochastic models that may be used to study problems related toenvironmental matters, in particular, air pollution. The impact of exposure toair pollutants on people's health is a very clearand well documented subject. Therefore, it is veryimportant to obtain ways to predict or explain the behaviour of pollutants in general. Dependingon the type of question that one is interested in answering, there are several ofways studying thatproblem. Among them we may quote, analy sis of the time series of the pollutants' measurements,analysis of the information obtained directly from the data, for instance, daily, weekly or monthlyaverages andstandard deviations. Another way to study the behaviour of pollutants in general isthroug h mathematical models. In the mathematical framework we may have for instance deterministic or stochastic models. The type of models that we aregoing to consider in this brief are thestochastic ones
Note:Springer eBooks
ISBN:9781461446453
Series:e-books
Series:SpringerLink (Online service)
Series:SpringerBriefs in Mathematics, 2191-8198
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Distribution (Probability theory) , Environmental protection
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Call number:SPRINGER-2013-9781461443469:ONLINE Show nearby items on shelf
Title:Continuous-Time Markov Chains and Applications [electronic resource] : A Two-Time-Scale Approach
Author(s): G. George Yin
Qing Zhang
Date:2013
Edition:Second edition
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
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Note:Springer 2013 e-book collections
Note:This book gives a systematic treatment of singularly perturbed systems that naturally arise in control and optimization, queueing networks, manufacturing systems, and financial engineering. It presents results on asymptoticexpansions of solutions of Komogorov forward and backward equations, properties of functional occupation measures, exponential upper bounds, and functional limit results for Markov chains with weak and strong interactions. To bridgethe gap between theory and applications, a large p ortion of the book is devoted to applications in controlled dynamic systems, production planning, and numerical methods for controlled Markovian systems with large-scale and complexstructures in the real-world problems. This second edition has been update d throughout and includes two new chapters on asymptotic expansions of solutions for backward equations and hybrid LQG problems. The chapters on analytic andprobabilistic properties of two-time-scale Markov chains have been almost completely rewritten and the notation has been streamlined and simplified. This book is written for applied mathematicians, engineers, operations researchers,and applied scientists. Selected material from the book can also be used for a one semester advanced graduate-level cours e in applied probability and stochastic processes
Note:Springer eBooks
Contents:Prologue and Preliminaries: Introduction and overview
Mathematical preliminaries
Markovian models
Two
Time
Scale Markov Chains: Asymptotic Expansions of Solutions for Forward Equations
Occupation Measures: Asymptotic Properties and Ramification
Asymptotic Expansions of Solutions for Backward Equations
Applications:MDPs, Near
optimal Controls, Numerical Methods, and LQG with Switching: Markov Decision Problems
Stochastic Control of Dynamical Systems
Numerical Methods for Control and Optimization
Hybrid LQG Problems
References
Index
ISBN:9781461443469
Series:e-books
Series:SpringerLink (Online service)
Series:Stochastic Modelling and Applied Probability, 0172-4568 : v37
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Mathematical optimization , Distribution (Probability theory) , Engineering mathematics
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Call number:SPRINGER-2013-9781461440574:ONLINE Show nearby items on shelf
Title:Informal Introduction to Stochastic Processes with Maple [electronic resource]
Author(s): Jan Vrbik
Paul Vrbik
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:The book presents an introduction to Stochastic Processes including Markov Chains, Birth and Death processes, Brownian motion andAutoregressive models. The emphasis is on simplifying both the underlying mathematics and theconceptual understanding of random processes. In particular, non-trivial computations are delegated to a computer-algebra system, specifically Maple (although other systems can be easily substituted). Moreover, great care istaken to properly introduce the required mathematical tools (such as difference equations and generating functions) so that even students with only a basic mathematical background will find the book self-contained. Manydetailed examples are given throughout the text to facilitate and reinforce learning. Jan Vrbik has been a Professor of Mathematics and Statistics at Brock University in St Catharines, Ontario, Canada, since 1982. Paul Vrbik iscurrently a PhD candidate in Computer Science at the University of Western Ontario in London, Ontario, Canada
Note:Springer eBooks
Contents:Contents
Preface
Finite Markov Chains
Finite Markov Chains II
Branching Processes
Renewal Theory
Poisson Process
Birth and Death Processes I
Birth and Death Processes II
Continuous
Time Markov Chains
Brownian Motion
Autoregressive Models
Basic Probability Review
Maple Programming
References
ISBN:9781461440574
Series:e-books
Series:SpringerLink (Online service)
Series:Universitext, 0172-5939
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Distribution (Probability theory) , Mathematical statistics
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Call number:SPRINGER-2012-9788847028234:ONLINE Show nearby items on shelf
Title:Selected Aspects of Fractional Brownian Motion [electronic resource]
Author(s): Ivan Nourdin
Date:2012
Publisher:Milano : Springer Milan : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Fractional Brownian motion (fBm) is a stochastic process which deviates significantly from Brownian motion and semimartingales, and others classically used in probability theory. As a centered Gaussian process, it ischaracterized by the stationarity of its increments and a medium- or long-memory property which is in sharp contrast with martingales and Markov processes. FBm has become a popular choice for applications where classical processescannot model these non-trivial properties for instance long memory, which is also known as persistence, is of fundamental importance for financial data and in internet traffic. The mathematical theory of fBm is currently beingdeveloped vigorously by a number of stochastic analysts, in various directions, using co mplementary and sometimes competing tools. This book is concerned with several aspects of fBm, including the stochastic integration with respect toit, the study of its supremum and its appearance as limit of partial sums involving stationary sequences, to name but a few. The book is addressed to researchers and graduate students in probability and mathematical statistics. Withvery few exceptions (where precise references are given), every stated result is proved
Note:Springer eBooks
Contents:1. Preliminaries
2. Fractional Brownian motion
3. Integration with respect to fractional Brownian motion
4. Supremum of the fractional Brownian motion
5. Malliavin calculus in a nutshell
6. Central limit theorem on the Wiener space
7. Weak convergence of partial sums of stationary sequences
8. Non
commutative fractional Brownian motion
ISBN:9788847028234
Series:e-books
Series:SpringerLink (Online service)
Series:B&SS Bocconi & Springer Series, 2039-1471
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Finance , Distribution (Probability theory)
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Call number:SPRINGER-2012-9783642299827:ONLINE Show nearby items on shelf
Title:Stochastic Analysis and Related Topics [electronic resource] : In Honour of Ali Sleyman stnel, Paris, June 2010
Author(s): Laurent Decreusefond
Jamal Najim
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:Since the early eighties, Ali Sleyman stnel has been one of the main contributors to the field of Malliavin calculus. In a workshop held in Paris, June 2010 several prominent researchers gave exciting talks in honor of his60th birthday. The present v olume includes scientific contributions from this workshop. Probability theory is first and foremost aimed at solving real-life problems containing randomness. Markov processes are one of the key tools formodeling that plays a vital part concerning such p roblems. Contributions on inventory control, mutation-selection in genetics and public-private partnerships illustrate several applications in this volume. Stochastic differentialequations, be they partial or ordinary, also play a key role in stochastic m odeling. Two of the contributions analyze examples that share a focus on probabilistic tools, namely stochastic analysis and stochastic calculus. Three otherpapers are devoted more to the theoretical development of these aspects. The volume addresses grad uate students and researchers interested in stochastic analysis and its applications
Note:Springer eBooks
Contents:1.Boubacar Bah, Etienne Pardoux and Ahmadou Bamba Sow: A lookdown model with selection
2.Alain Bensoussan: Control of Inventories with Markov Demand
3.Zdzisaw Brzezniak and Annie Millet: On the splitting method for some complex
valued quasilinear evolution equations
4. Caroline Hillairet and Monique Pontier: A Modelisation of Public Private Parternships with failure time
5.Joseph Najnudel, Daniel Stroock and Marc Yor: On a flow of transformations of a Wiener space
6.Nicolas Privault: Measure invariance on the Lie
Wiener path space
7.Denis Talay: Derivatives of Solutions
ISBN:9783642299827
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Proceedings in Mathematics & Statistics, 2194-1009 : v22
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Differential Equations , Differential equations, partial , Genetics Mathematics , Distribution (Probability theory)
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Call number:SPRINGER-2012-9783642298806:ONLINE Show nearby items on shelf
Title:Fluctuations in Markov Processes [electronic resource] : Time Symmetry and Martingale Approximation
Author(s): Tomasz Komorowski
Claudio Landim
Stefano Olla
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:Diffusive phenomena in statistical mechanics and in other fields arise from markovian modeling and their study requires sophisticated mathematical tools. In infinite dimensional situations, time symmetry properties can beexploited in order to make ma rtingale approximations, along the lines of the seminal work of Kipnis and Varadhan. The present volume contains the most advanced theories on the martingale approach to central limit theorems. Using thetime symmetry properties of the Markov processes, th e book develops the techniques that allow us to deal with infinite dimensional models that appear in statistical mechanics and engineering (interacting particle systems,homogenization in random environments, and diffusion in turbulent flows, to mention ju st a few applications). The first part contains a detailed exposition of the method, and can be used as a text for graduate courses. The secondconcerns application to exclusion processes, in which the duality methods are fully exploited. The third part is about the homogenization of diffusions in random fields, including passive tracers in turbulent flows (including thesuperdiffusive behavior). There are no other books in the mathematical literature that deal with this kind of approach to the problem of the central limit theorem. Hence, this volume meets the demand for a monograph on this powerfulapproach, now widely used in many areas of probability and mathematical physics. The book also covers the connections with and application to hydrodynamic limit s and homogenization theory, so besides probability researchers it willalso be of interest to mathematical physicists and analysts
Note:Springer eBooks
Contents:Preface
Part I: General Theory
1.A Warming
up Example
2.Central Limit Theorems
3.RandomWalks in Random Environment
4.Bounds and Variational Principles for the Asymptotic Variance
Part II: Simple Exclusion Processes
5.The Simple Exclusion Process
6.Self Diffusion
7.Equilibrium Fluctuations of the Density Field
8.Regularity of the Asymptotic Variance
Part III: Diffusions in Random Environments
10.Variational Principles for the Limiting Variance
11.Diffusions with Divergence Free Drifts
12.Diffusions with Gaussian Drifts
13.Ornstein
Uhlenbeck Process w
ISBN:9783642298806
Series:e-books
Series:SpringerLink (Online service)
Series:Grundlehren der mathematischen Wissenschaften, A Series of Comprehensive Studies in Mathematics, 0072-7830 : v345
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Distribution (Probability theory)
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Call number:SPRINGER-2012-9783642284397:ONLINE Show nearby items on shelf
Title:Stochastic Models in Life Insurance [electronic resource]
Author(s): Michael Koller
Date:2012
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
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Note:The book provides a sound mathematical base for life insurance mathematics and applies the underlying concepts to concrete examples. Moreover the models presented make it possible to model life insurance policies by means ofMarkov chains. Two chapter s covering ALM and abstract valuation concepts on the background of Solvency II complete this volume. Numerous examples and a parallel treatment of discrete and continuous approaches help the reader toimplement the theory directly in practice
Note:Springer eBooks
Contents:1. A general life insurance model
2. Stochastic processes
3. Interest rate
4. Cash flows and the mathematical reserve
5. Difference equations and differential equations
6. Examples and problems from applications
7. Hattendorff's Theorem
8. Unit
linked policies
9. Policies with stochastic interest rate
10. Technical analysis
11. Abstract valuation
12. Policyholder bonus mechanism
A. Notes on stochastic integration
B. Examples
C. Mortality rates in Germany
D. Mortality rates in Switzerland
E. Java code for the calculation of the Markov model
Ref
ISBN:9783642284397
Series:e-books
Series:SpringerLink (Online service)
Series:EAA Series, 1869-6929
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Distribution (Probability theory) , Economics Statistics
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Call number:SPRINGER-2012-9783642274619:ONLINE Show nearby items on shelf
Title:Sminaire de Probabilits XLIV [electronic resource]
Author(s): Catherine Donati-Martin
Antoine Lejay
Alain Rouault
Date:2012
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
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Note:As usual, some of the contributions to this 44th Sminaire de Probabilits were presented during the Journes de Probabilits held in Dijon in June 2010. The remainder were spontaneous submissions or were solicited by theeditors. The traditional and hist orical themes of the Sminaire are covered, such as stochastic calculus, local times and excursions, and martingales. Some subjects already touched on in the previous volumes are still here: freeprobability, rough paths, limit theorems for general processe s (here fractional Brownian motion and polymers), and large deviations. Lastly, this volume explores new topics, including variable length Markov chains and peacocks. We hopethat the whole volume is a good sample of the main streams of current research on probability and stochastic processes, in particular those active in France
Note:Springer eBooks
Contents:Context trees, variable length Markov chains and dynamical sources
Martingale property of generalized stochastic exponentials
Some classes of proper integrals and generalized Ornstein
Uhlenbeck processes
Martingale representations for diffusion processes and backward stochastic differential equations
Quadratic Semimartingale BSDEs Under an Exponential Moments Condition
The derivative of the intersection local time of Brownian motion through Wiener chaos
On the occupation times of Brownian excursions and Brownian loops
Discrete approximation to solution flows of Tanakas
ISBN:9783642274619
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Mathematics, 0075-8434 : v2046
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Distribution (Probability theory)
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Call number:SPRINGER-2012-9783642258473:ONLINE Show nearby items on shelf
Title:Random Perturbations of Dynamical Systems [electronic resource]
Author(s): Mark I Freidlin
Alexander D Wentzell
Date:2012
Edition:3rd ed. 2012
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
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Note:Many notions and results presented in the previous editions of this volume have since become quite popular in applications, and many of them have been rediscovered in applied papers. In the present 3rd edition smallchanges were made to the chapters in which long-time behavior of the perturbed system is determined by large deviations. Most of these changes concern terminology. In particular, it is explained that the notion of sub-limitingdistribution for a given initial point and a time scale is iden tical to the idea of metastability, that the stochastic resonance is a manifestation of metastability, and that the theory of this effect is a part of the large deviationtheory. The reader will also find new comments on the notion of quasi-potential that the authors introduced more than forty years ago, and new references to recent papers in which the proofs of some conjectures included in previouseditions have been obtained. Apart from the above mentioned changes the main innovations in the 3rd edition concern the averaging principle. A new Section on deterministic perturbations of one-degree-of-freedom systems was added inChapter 8. It is shown there that pure deterministic perturbations of an oscillator may lead to a stochastic, in a certain sense, lo ng-time behavior of the system, if the corresponding Hamiltonian has saddle points. The usefulness of ajoint consideration of classical theory of deterministic perturbations together with stochastic perturbations is illustrated in this section. Also a new Chapter 9 has been inserted in which deterministic and stochastic perturbations ofsystems with many degrees of freedom are considered. Because of the resonances, stochastic regularization in this case is even more important
Note:Springer eBooks
Contents:1.Random Perturbations
2.Small Random Perturbations on a Finite Time Interval
3.Action Functional
4.Gaussian Perturbations of Dynamical Systems. Neighborhood of an Equilibrium Point
5.Perturbations Leading to Markov Processes
6.Markov Perturbations on Large Time Intervals
7.The Averaging Principle. Fluctuations in Dynamical Systems with Averaging
8.Random Perturbations of Hamiltonian Systems
9. The Multidimensional Case
10.Stability Under Random Perturbations
11.Sharpenings and Generalizations
References
Index
ISBN:9783642258473
Series:e-books
Series:SpringerLink (Online service)
Series:Grundlehren der mathematischen Wissenschaften, A Series of Comprehensive Studies in Mathematics, 0072-7830 : v260
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Distribution (Probability theory)
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Call number:SPRINGER-2012-9783642232800:ONLINE Show nearby items on shelf
Title:Stochastic Stability of Differential Equations [electronic resource]
Author(s): Rafail Khasminskii
Date:2012
Edition:Completely Revised and Enlarged 2nd Edition
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
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Note:Since the publication of the first edition of the present volume in 1980, the stochastic stability of differential equations has become a very popular subject of research in mathematics and engineering. To date exact formulas forthe Lyapunov exponent , the criteria for the moment and almost sure stability, and for the existence of stationary and periodic solutions of stochastic differential equations have been widely used in the literature. In this updatedvolume readers will find important new results on the moment Lyapunov exponent, stability index and some other fields, obtained after publication of the first edition, and a significantly expanded bibliography. This volume provides asolid foundation for students in graduate courses in mathematics and its applications. It is also useful for those researchers who would like to learn more about this subject, to start their research in this area or to study theproperties of concrete mechanical systems subjected to random perturbations
Note:Springer eBooks
Contents:Boundedness in Probability and Stability of Stochastic Processes Defined by Differential Equations
2.Stationary and Periodic Solutions of Differential Equations. 3.Markov Processes and Stochastic Differential Equations
4.Ergodic Properties of Solutions of Stochastic Equations
5.Stability of Stochastic Differential Equations
6.Systems of Linear Stochastic Equations
7.Some Special Problems in the Theory of Stability of SDEs
8.Stabilization of Controlled Stochastic Systems
A. Appendix to the First English Edition
B. Appendix to the Second Edition. Moment Lyapunov Expone
ISBN:9783642232800
Series:e-books
Series:SpringerLink (Online service)
Series:Stochastic Modelling and Applied Probability, 0172-4568 : v66
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Distribution (Probability theory) , Mechanics
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Call number:SPRINGER-2012-9783034802406:ONLINE Show nearby items on shelf
Title:Associated Sequences, Demimartingales and Nonparametric Inference [electronic resource]
Author(s): B.L.S Prakasa Rao
Date:2012
Publisher:Basel : Springer Basel
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book gives a comprehensive review of results for associated sequences and demimartingales developed so far, with special emphasis on demimartingales and related processes. One of the basic aims of theory of probability andstatistics is to build stochastic models which explain the phenomenon under investigation and explore the dependence among various covariates which influence this phenomenon. Classic examples are the concepts of Markov dependence or ofmixing for random processes. Esary, Prosch an and Walkup introduced the concept of association for random variables, and Newman and Wright studied properties of processes termed as demimartingales. It can be shown that the partial sumsof mean zero associated random variables form a demimartingale. Probabilistic properties of associated sequences, demimartingales and related processes are discussed in the first six chapters. Applications of some of these resultsto problems in nonparametric statistical inference for such processes are investigated in the last three chapters. This book will appeal to graduate students and researchers interested in probabilistic aspects of various types ofstochastic processes and their applications in reliability theory, statistical mechanics, percolation theory and other areas
Note:Springer eBooks
Contents:Preface
Associated Random Variables and Related Concepts
Demimartingales
N
Demimartingales
Conditional Demimartingales
Multidimensionally Indexed Demimartingales and Continuous Parameter Demimartingales
Limit Theorems for Associated Random Variables
Nonparametric Estimation for Associated Sequences
Nonparametric Tests for Associated Sequences
Nonparametric Tests for Change in Marginal Density Function for Associated Sequences
References
Index
ISBN:9783034802406
Series:e-books
Series:SpringerLink (Online service)
Series:Probability and its Applications
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Distribution (Probability theory)
Availability:Click here to see Library holdings or inquire at Circ Desk (x3401)
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