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AdMit: Adaptive Mixture of Student-t Distributions

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 ORCID iD [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

Documentation:

Reference manual: AdMit.pdf

Downloads:

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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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