Provides functions to perform the fitting of an adaptive mixture of Student-t distributions to a target density through its kernel function as described in Ardia et al. (2009) <doi:10.18637/jss.v029.i03>. The mixture approximation can then be used as the importance density in importance sampling or as the candidate density in the Metropolis-Hastings algorithm to obtain quantities of interest for the target density itself.
Version: | 2.1.9 |
Depends: | mvtnorm |
Suggests: | coda |
Published: | 2022-02-08 |
Author: | David Ardia [aut, cre, cph], Lennart Hoogerheide [ctb], Herman van Dijk [ctb] |
Maintainer: | David Ardia <david.ardia.ch at gmail.com> |
BugReports: | https://github.com/ArdiaD/AdMit/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
Copyright: | see file COPYRIGHTS |
URL: | https://github.com/ArdiaD/AdMit |
NeedsCompilation: | yes |
Citation: | AdMit citation info |
Materials: | README NEWS |
In views: | Bayesian, Cluster, Distributions |
CRAN checks: | AdMit results |
Reference manual: | AdMit.pdf |
Package source: | AdMit_2.1.9.tar.gz |
Windows binaries: | r-devel: AdMit_2.1.9.zip, r-release: AdMit_2.1.9.zip, r-oldrel: AdMit_2.1.9.zip |
macOS binaries: | r-release (arm64): AdMit_2.1.9.tgz, r-oldrel (arm64): AdMit_2.1.9.tgz, r-release (x86_64): AdMit_2.1.9.tgz, r-oldrel (x86_64): AdMit_2.1.9.tgz |
Old sources: | AdMit archive |
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