Marc has two books out: 1. Introduction to WinBUGS for Ecologists: Bayesian approach to regression, ANOVA, mixed models and related analyses 2. Bayesian Population Analysis using WinBUGS: A hierarchical perspective
I have the first and I probably reference it once a week. I'm not a statistician (just a "wannabe") but I find this book the most useful. If you use it as a tutorial, you create data, then analyze it using R and WinBUGS. So you're able to compare standard statistical analyses with Bayesian results. I've also read McCarthy's book. This is a very nice introduction to the Bayesian approach and I would read this first. Cheers, Jeff ***************************************** Jeffrey A. Stratford, Ph.D. Department of Health and Biological Sciences 84 W. South St. Wilkes Univertsity, PA 18766 570-332-2942 http://web.wilkes.edu/jeffrey.stratford/ ***************************************** -----Original Message----- From: r-sig-ecology-boun...@r-project.org [mailto:r-sig-ecology-boun...@r-project.org] On Behalf Of Ben Bolker Sent: Saturday, November 26, 2011 3:35 PM To: r-sig-ecology@r-project.org Subject: Re: [R-sig-eco] papers about using MCMC in ecological study Jakub Szymkowiak <qbaszym@...> writes: > > Duncan, Rob, Peter - thanks a lot for suggestions about literature! > > Peter - by MCMC methods I mean Markov Chain Monte Carlo ;) > I have great book by Ben Bolker - Ecological Models and Data in R, but I'm > searching for more examples of using MCMC in the study of habitat selection. > Anyway - thanks for Your advice! (1) Michael McCarthy's book on Bayesian methods (the best/gentlest introduction to WinBUGS/Bayesian methods for ecologists) (2) Royle and Dorazio's book (3) maybe Marc Kéry's new book (haven't read it) _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology