An explicit formula for a posterior distribution is not something to expect from an MCMC procedure. But the next best thing to an explicit formula for a posterior distribution is a zillion samples from that distribution (which is what you have).
What you can do is display smooth representations of the individual marginal distributions (and bivariate marginal distributions) using the density function or functions in the KernSmooth and ks packages. Jim Jim Baldwin Station Statistician Pacific Southwest Research Station USDA Forest Service -----Original Message----- From: r-sig-ecology-boun...@r-project.org [mailto:r-sig-ecology-boun...@r-project.org] On Behalf Of ? Sent: Friday, January 17, 2014 5:57 AM To: r-sig-ecology Subject: [R-sig-eco] joint distribution Dear All I get samples from MCMC sampling to a posterior distribution. there is four variables, how could I get a joint distribution for this four variable from the samples? Thanks in advance~! Han 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 This electronic message contains information generated by the USDA solely for the intended recipients. Any unauthorized interception of this message or the use or disclosure of the information it contains may violate the law and subject the violator to civil or criminal penalties. If you believe you have received this message in error, please notify the sender and delete the email immediately. _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
