On 01/18/2014 04:39 AM, 明 wrote:
Have you checked for convergence? If the chains are giving different marginal distributions, this suggests they haven't converged, so they are not sampling from the correct posterior distribution (or, at least, some chains aren't).Dear all I have a model with four paramters, I want to estimate the parameter uncertainty, so Bayesian analysis with MCMC method is applied. But every sigle mcmc chain seems give quite different parameter marginal distributions. In order to get the true parameter marginal distributions, I do like this: (1) I take 100 MCMC chain, and each chain has 10000 iterations. (2) caculate the different parameter marginal distributions according to the frequence of paramter in step 1 sampling. The result seems reasonable. but is it right? Looking forward for your reply, Thanks in advanceHan Ming[[alternative HTML version deleted]]_______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Bob -- Bob O'Hara Biodiversity and Climate Research Centre Senckenberganlage 25 D-60325 Frankfurt am Main, Germany Tel: +49 69 7542 1863 Mobile: +49 1515 888 5440 WWW: http://www.bik-f.de/root/index.php?page_id=219 Blog: http://blogs.nature.com/boboh Journal of Negative Results - EEB: www.jnr-eeb.org _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
