Ecological Models and Data in R

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Princeton University Press, Jul 21, 2008 - Computers - 396 pages
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Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R. Drawing on extensive experience teaching these techniques to graduate students in ecology, Benjamin Bolker shows how to choose among and construct statistical models for data, estimate their parameters and confidence limits, and interpret the results. The book also covers statistical frameworks, the philosophy of statistical modeling, and critical mathematical functions and probability distributions. It requires no programming background--only basic calculus and statistics.

  • Practical, beginner-friendly introduction to modern statistical techniques for ecology using the programming language R
  • Step-by-step instructions for fitting models to messy, real-world data
  • Balanced view of different statistical approaches
  • Wide coverage of techniques--from simple (distribution fitting) to complex (state-space modeling)
  • Techniques for data manipulation and graphical display
  • Companion Web site with data and R code for all examples
 

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Contents

1 Introduction and Background
1
2 Exploratory Data Analysis and Graphics
29
3 Deterministic Functions for Ecological Modeling
72
4 Probability and Stochastic Distributions for Ecological Modeling
103
5 Stochastic Simulation and Power Analysis
147
6 Likelihood and All That
169
7 Optimization and All That
222
8 Likelihood Examples
263
10 Modeling Variance
316
11 Dynamic Models
337
12 Afterword
362
Appendix Algebra and Calculus Basics
363
Bibliography
369
Index of R Arguments Functions and Packages
383
General Index
389
Copyright

9 Standard Statistics Revisited
298

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