Multivariate posterior distribution with gaussian approximation, using R.

Abstract

In bayesian statistical inference the posterior probability distribution of unknown model parameters is of central importance. This paper uses the tools of the R language to obtain simulated posterior samples as an approximated Gaussian multivariate distribution. The method is illustrated with inference for the Schnute growth curve and applied to the fransciscana dolphin (Pontoporia blainvillei) from southern Brazil.