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AdMit: Adaptive Mixtures of Student-t Distributions

David Ardia, Lennart Hoogerheide and Herman van Dijk

No 10, DQE Working Papers from Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland

Abstract: 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.

Keywords: adaptive mixture; Student-t distributions; importance sampling; independence chain Metropolis-Hastings algorithm; Bayesian inference; R software. (search for similar items in EconPapers)
JEL-codes: C01 C11 C15 (search for similar items in EconPapers)
Pages: 6 pages
Date: 2008-08-01, Revised 2009-01-07
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Citations: View citations in EconPapers (14) Track citations by RSS feed

Published in The R Journal, 2009, vol. 1, no. 1, pp.25--31.

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