Adaptive mixture of Student-t distributions
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).
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.