Bringing Bayesian Models to Life
About this ebook
Features:
- R code implementing algorithms to fit Bayesian models using real and simulated data examples.
- A comprehensive review of statistical models commonly used in ecological and environmental science.
- Overview of Bayesian computational methods such as importance sampling, MCMC, and HMC.
- Derivations of the necessary components to construct statistical algorithms from scratch.
Bringing Bayesian Models to Life contains a comprehensive treatment of models and associated algorithms for fitting the models to data. We provide detailed and annotated R code in each chapter and apply it to fit each model we present to either real or simulated data for instructional purposes. Our code shows how to create every result and figure in the book so that readers can use and modify it for their own analyses. We provide all code and data in an organized set of directories available at the authors' websites.
About the author
Mevin B. Hooten is a Professor in the Departments of Fish, Wildlife, & Conservation Biology and Statistics at Colorado State University. He is also Assistant Unit Leader of the Colorado Cooperative Fish and Wildlife Research Unit (U.S. Geological Survey) and a Fellow of the American Statistical Association. He earned his PhD in Statistics at the University of Missouri and focuses on the development of statistical methodology for spatial and spatio-temporal ecological processes.
Trevor J. Hefley is an Assistant Professor in the Department of Statistics at Kansas State University. He earned a PhD in Statistics and Natural Resource Science at the University of Nebraska - Lincoln and focuses on developing and applying spatiotemporal statistical methods to inform conservation and management of fish and wildlife populations.
