AdMit: Adaptive mixtures of Student-t distributions

David Ardia, Lennart Hoogerheide & Herman Van Dijk

Abstract This short note presents the R package AdMit which provides flexible functions to approximate a certain target distribution and it provides an efficient 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.
Keywords Adaptive mixture, Student-t distributions, importance sampling, independence chain Metropolis-Hasting algorithm, Bayesian, R software
Citation Ardia, D., Hoogerheide, L., & Van Dijk , H. (2009). AdMit: Adaptive mixtures of Student-t distributions. The R Journal, 1(1), 25-30.
Type Journal article (English)
Date of appearance 2009
Journal The R Journal
Volume 1
Issue 1
Pages 25-30
URL https://journal.r-project.org/archive/2009-1/RJournal_200...
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