Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan
eBook - ePub

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

  1. 328 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

About this book

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data.Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces Bayesian software, using R for the simple modes, and flexible Bayesian software (BUGS and Stan) for the more complicated ones. Guiding the ready from easy toward more complex (real) data analyses ina step-by-step manner, the book presents problems and solutions—including all R codes—that are most often applicable to other data and questions, making it an invaluable resource for analyzing a variety of data types.- Introduces Bayesian data analysis, allowing users to obtain uncertainty measurements easily for any derived parameter of interest- Written in a step-by-step approach that allows for eased understanding by non-statisticians- Includes a companion website containing R-code to help users conduct Bayesian data analyses on their own data- All example data as well as additional functions are provided in the R-package blmeco

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Yes, you can access Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan by Franzi Korner-Nievergelt,Tobias Roth,Stefanie von Felten,Jérôme Guélat,Bettina Almasi,Pius Korner-Nievergelt in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Ecology. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Academic Press
Year
2015
Print ISBN
9780128013700
eBook ISBN
9780128016787
Topic
Biological Sciences
Subtopic
Ecology
Index
Biological Sciences

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Digital Assets
  6. Acknowledgments
  7. Chapter 1. Why do we Need Statistical Models and What is this Book About?
  8. Chapter 2. Prerequisites and Vocabulary
  9. Chapter 3. The Bayesian and the Frequentist Ways of Analyzing Data
  10. Chapter 4. Normal Linear Models
  11. Chapter 5. Likelihood
  12. Chapter 6. Assessing Model Assumptions: Residual Analysis
  13. Chapter 7. Linear Mixed Effects Models
  14. Chapter 8. Generalized Linear Models
  15. Chapter 9. Generalized Linear Mixed Models
  16. Chapter 10. Posterior Predictive Model Checking and Proportion of Explained Variance
  17. Chapter 11. Model Selection and Multimodel Inference
  18. Chapter 12. Markov Chain Monte Carlo Simulation
  19. Chapter 13. Modeling Spatial Data Using GLMM
  20. Chapter 14. Advanced Ecological Models
  21. Chapter 15. Prior Influence and Parameter Estimability
  22. Chapter 16. Checklist
  23. Chapter 17. What Should I Report in a Paper
  24. References
  25. Index