Description

<p><i>Bayesian Data Analysis in Ecology Using Linear Models</i> <i>with R, BUGS, and STAN </i>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. <i>Bayesian Data Analysis in Ecology Using Linear Models</i> <i>with R, BUGS, and STAN </i>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.</p><br><br><ul> <ul></ul><li>Introduces Bayesian data analysis, allowing users to obtain uncertainty measurements easily for any derived parameter of interest</li><li>Written in a step-by-step approach that allows for eased understanding by non-statisticians</li><li>Includes a companion website containing R-code to help users conduct Bayesian data analyses on their own data</li><li>All example data as well as additional functions are provided in the R-package <i>blmeco</i></li></ul>