Ardia, David Hoogerheide, Lennart F. van Dijk, Herman K. 2009 This short note presents the R package AdMit which provides flexible functions to approximate a certain target distribution and to efficiently generate a sample of random draws from it, given only a kernel of the target density function. The estimation procedure is fully automatic and thus avoids the time-consuming and difficult task of tuning a sampling algorithm. To illustrate the use of the package, we apply the AdMit methodology to a bivariate bimodal distribution. We describe the use of the functions provided by the package and document the ability and relevance of the methodology to reproduce the shape of non-elliptical distributions. application/pdf https://folia.unifr.ch/global/documents/302739 https://folia.unifr.ch/documents/302739/files/WP_DQE_10.pdf eng info:eu-repo/semantics/openAccess License undefined adaptive mixture Student-t distributions importance sampling independence chain Metropolis-Hastings algorithm Bayesian inference R software info:eu-repo/classification/udc/33 The AdMit Package http://purl.org/coar/resource_type/c_18ws