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SPIRES-BOOKS: FIND KEYWORD FORESTS AND FORESTRY *END*INIT* use /tmp/qspiwww.webspi1/5294.247 QRY 131.225.70.96 . find keyword forests and forestry ( in books using www Cover
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Call number:SPRINGER-2011-9781441979766:ONLINE Show nearby items on shelf
Title:Numerical Ecology with R [electronic resource]
Author(s): Daniel Borcard
Francois Gillet
Pierre Legendre
Date:2011
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Numerical Ecology with R provides a long-awaited bridge between a textbook in Numerical Ecology and the implementation of this discipline in the R language. After short theoretical overviews, the authors accompany the usersthrough the exploration of the methods by means of applied and extensively commented examples. Users are invited to use this book as a teaching companion at the computer. The travel starts with exploratory approaches, proceeds with theconstruction of associationmatrices, then addre sses three families of methods: clustering, unconstrained and canonical ordination,and spatial analysis. All the necessary data files, the scripts used in the chapters, as well as theextra R functions and packages written by the authors, can be downloaded from a web page accessible through the Springer web site(http://adn.biol.umontreal.ca/~numericalecology/numecolR/). This book is aimed at professionalresearchers, practitioners, graduate students and teachers in ecology, environmental science and enginee ring, and in related fields such as oceanography, molecular ecology, agriculture and soil science, who already have a background ingeneral and multivariate statistics and wish to apply this knowledge to their data using the R language, as well as people w illing to accompany their disciplinary learning with practical applications. People from other fields (e.g.geology, geography, paleoecology, phylogenetics, anthropology, the social and education sciences, etc.) may also benefit from the materials presente d in this book. The three authors teach numerical ecology, both theoretical andpractical, to a wide array of audiences, in regular courses in their Universities and in short courses given around the world. Daniel Borcard is lecturer of Biostatistics and E cology and researcher in Numerical Ecology at Universitde Montral, Qubec, Canada. Franois Gillet is professor of Community Ecology and Ecological Modelling at Universit de Franche-Comt,
Note:Springer eBooks
Contents:Introduction
Exploratory data analysis
Association measures and matrices
Cluster analysis
Unconstrained ordination
Canonical ordination
Spatial analysis of ecological data
ISBN:9781441979766
Series:e-books
Series:SpringerLink (Online service)
Series:Use R
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Epidemiology , Statistical methods , Ecology , Forests and forestry
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Call number:SPRINGER-2011-9781441977625:ONLINE Show nearby items on shelf
Title:Forest Analytics with R [electronic resource] : An Introduction
Author(s): Andrew P Robinson
Jeff D Hamann
Date:2011
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Forest Analytics with R combines practical, down-to-earth forestry data analysis and solutions to real forest management challenges with state-of-the-art statistical and data-handling functionality. The authors adopt aproblem-driven approach, in whic h statistical and mathematical tools are introduced in the context of the forestry problem that they can help to resolve. All the tools are introduced in the context of real forestry datasets, whichprovide compelling examples of practical applications. Th e modeling challenges covered within the book include imputation and interpolation for spatial data, fitting probability density functions to tree measurement data using maximumlikelihood, fitting allometric functions using both linear and non-linear leas t-squares regression, and fitting growth models using both linear and non-linear mixed-effects modeling. The coverage also includes deploying and usingforest growth models written in compiled languages, analysis of natural resources and forestry inventory data, and forest estate planning and optimization using linear programming. The book would be ideal for a one-semester class inforest biometrics or applied statistics for natural resources management. The text assumes no programming background, some intr oductory statistics, and very basic applied mathematics. Andrew Robinson has been associate professor offorest mensuration and forest biometrics at the University of Idaho, and is currently senior lecturer in applied statistics at the University of Melbou rne. He received his PhD in forestry from the University of Minnesota. Robinson isauthor of the popular and freely-available icebreakeR document. Jeff Hamann has been a software developer, forester, and financial analyst. He is currently a consultant spec ializing in forestry, operations research, and geographicinformation sciences. He received his PhD in forestry from Oregon State University. Both authors have presented numerous R workshops to forestr
Note:Springer eBooks
Contents:Introduction
Forest data management
Data analysis for common inventory methods
Imputation and Interpolation
Fitting dimensional distributions
Linear and non
linear models
Fitting linear hierarchical models
Simulations
Forest estate planning and optimization
ISBN:9781441977625
Series:e-books
Series:SpringerLink (Online service)
Series:Use R
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Forests and forestry , Environmental sciences
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Call number:SPRINGER-2009-9780387096162:ONLINE Show nearby items on shelf
Title:Nonlinear Regression with R [electronic resource]
Author(s): Christian Ritz
Jens Carl Streibig
Date:2009
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. Currently, R offers a wide range of functionality for nonlinear regression analysis, but the relevantfunctions, packages and documentation are scattered across the R environment. This book provides a coherent and unified treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology,chemistry, engineering, medicine and toxico logy. The book begins with an introduction on how to fit nonlinear regression models in R. Subsequent chapters explain in more depth the salient features of the fitting function nls(), the useof model diagnostics, the remedies for various model departures , and how to do hypothesis testing. In the final chapter grouped-data structures, including an example of a nonlinear mixed-effects regression model, are considered.Christian Ritz has a PhD in biostatistics from the Royal Veterinary and Agricultural Unive rsity. For the last 5 years he has been working extensively with various applications of nonlinear regression in the life sciences and relateddisciplines, authoring several R packages and papers on this topic. He is currently doing postdoctoral research a t the University of Copenhagen. Jens C. Streibig is a professor in Weed Science at the University of Copenhagen. He hasfor more than 25 years worked on selectivity of herbicides and more recently on the ecotoxicology of pesticides and has extensive experi ence in applying nonlinear regression models. Together with the first author he has developed shortcourses on the subject of this book for students in the life sciences
Note:Springer eBooks
Contents:Introduction
Getting started
Starting values and self starters
More on nls ()
Model diagnostics
Remedies for model variations
Uncertainty, hypothesis testing and model selection
Grouped data
Appendix A: Datasets and models
Appendix B: Self starter functions
Appendix C: Packages and functions
References
Index
ISBN:9780387096162
Series:e-books
Series:SpringerLink (Online service)
Series:Use R
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Toxicology , Epidemiology , Forests and forestry , Mathematical statistics , Engineering
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Call number:SPRINGER-2005-9783540268819:ONLINE Show nearby items on shelf
Title:Radioactivity Radionuclides Radiation [electronic resource] : Including the Universal Nuclide Chart on CD-ROM
Author(s): Joseph Magill
Jean Galy
Date:2005
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:RADIOACTIVITY RADIONUCLIDES RADIATION is suitable for a general audience interested in topical environmental and human health radiological issues such as radiation exposure in aircraft, food sterilisation, nuclearmedicine, radon gas, radiation disp ersion devices (dirty bombs) It leads the interested reader through the three Rs of nuclear science, to the forefront of research and developments in the field. The book is also suitable forstudents and professionals in the related disciplines of nuclear and radiochemistry, health physics, environmental sciences, nuclear and astrophysics. Recent developments in the areas of exotic decay modes (bound beta decay ofbare or fully ionized nuclei), laser transmutation, nuclear forensics, radiation hormesis and the LNT hypothesis are covered. Atomic mass data for over 3000 nuclides from the most recent (2003) evaluation are included
Note:Springer eBooks
Contents:Origins and Discoveries
Nuclear Energetics
Radioactivity and Nuclear Reactions
Types of Radioactive Decay
Basic Research
Archeology and Dating
Radioisotopes in Medicine
Radioisotopes in Industry
Radiation and the Environment
ISBN:9783540268819
Series:e-books
Series:SpringerLink (Online service)
Series:Physics and Astronomy (Springer-11651)
Keywords: Chemistry , Nuclear medicine , Agriculture , Forests and forestry , Nuclear fusion
Availability:Click here to see Library holdings or inquire at Circ Desk (x3401)
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