AdMit: Adaptive Mixtures of Student-t Distributions

The R Journal, Vol. 1, No. 1, pp. 25-30, May 2009

6 Pages Posted: 16 Jun 2010 Last revised: 3 Aug 2018

See all articles by David Ardia

David Ardia

HEC Montreal - Department of Decision Sciences

Lennart F. Hoogerheide

VU University Amsterdam

H. K. van Dijk

Tinbergen Institute; Econometric Institute

Date Written: May 1, 2009

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

JEL Classification: C11, C15

Suggested Citation

Ardia, David and Hoogerheide, Lennart F. and van Dijk, Herman K., AdMit: Adaptive Mixtures of Student-t Distributions (May 1, 2009). The R Journal, Vol. 1, No. 1, pp. 25-30, May 2009, Available at SSRN: https://ssrn.com/abstract=1625945

David Ardia (Contact Author)

HEC Montreal - Department of Decision Sciences ( email )

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Lennart F. Hoogerheide

VU University Amsterdam ( email )

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Herman K. Van Dijk

Tinbergen Institute ( email )

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Econometric Institute ( email )

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