Adaptive mixture of Student-t distributions

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AdMit (Ardia et al., 2009a) is an R package 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 core algorithm fits an adaptive mixture of Student-t distributions to the density of interest, and then, importance sampling or the independence chain Metropolis-Hastings algorithm is used to obtain quantities of interest for the target density, using the fitted mixture as the importance or candidate density. The estimation procedure is fully automatic and thus avoids the time-consuming and difficult task of tuning a sampling algorithm. Full description of the algorithm and numerous applications are available in Ardia et al. (2009a) and Ardia et al. (2009b).

Please cite AdMit in publications:

Ardia, D., Hoogerheide, L., van Dijk, H.K. (2009a).
Adaptive mixture of Student-t distributions as a flexible candidate distribution for efficient simulation: The R package AdMit.
Journal of Statistical Software 29(3), pp.1-32.

Ardia, D., Hoogerheide, L., van Dijk, H.K. (2009b).
AdMit: Adaptive mixture of Student-t distributions.
R Journal 1(1), pp.25-30.