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
Date Written: May 1, 2009
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: Suggested Citation