Bringing Bayesian Models to Life

Book Description

Bringing Bayesian to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data . We open the black box and show the reader how to connect modern statistical models to computer . These allow the user to fit models that answer their questions without needing to rely on automated Bayesian . We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models.


  • R 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.

Book Details

  • Title: Bringing Bayesian Models to Life
  • Author: ,
  • Length: 590 pages
  • Edition: 1
  • Language: English
  • Publisher:
  • Publication Date: 2019-06-11
  • ISBN-10: 0367198487
  • ISBN-13: 9780367198480

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