Package: Nmix 2.0.5

Nmix: Bayesian Inference on Univariate Normal Mixtures

A program for Bayesian analysis of univariate normal mixtures with an unknown number of components, following the approach of Richardson and Green (1997) <doi:10.1111/1467-9868.00095>. This makes use of reversible jump Markov chain Monte Carlo methods that are capable of jumping between the parameter sub-spaces corresponding to different numbers of components in the mixture. A sample from the full joint distribution of all unknown variables is thereby generated, and this can be used as a basis for a thorough presentation of many aspects of the posterior distribution.

Authors:Peter Green [aut, cre]

Nmix_2.0.5.tar.gz
Nmix_2.0.5.zip(r-4.7)Nmix_2.0.5.zip(r-4.6)Nmix_2.0.5.zip(r-4.5)
Nmix_2.0.5.tgz(r-4.6-x86_64)Nmix_2.0.5.tgz(r-4.6-arm64)Nmix_2.0.5.tgz(r-4.5-x86_64)Nmix_2.0.5.tgz(r-4.5-arm64)
Nmix_2.0.5.tar.gz(r-4.7-arm64)Nmix_2.0.5.tar.gz(r-4.7-x86_64)Nmix_2.0.5.tar.gz(r-4.6-arm64)Nmix_2.0.5.tar.gz(r-4.6-x86_64)
Nmix_2.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
Nmix/json (API)

# Install 'Nmix' in R:
install.packages('Nmix', repos = c('https://petergreen5678.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • enz - Enzyme data set
  • galx - Galaxy data set
  • lnacid - Lake acidity data set

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

fortran

1.00 score 214 downloads 6 exports 0 dependencies

Last updated from:22a27ea53c. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK137
linux-devel-x86_64OK118
source / vignettesOK177
linux-release-arm64OK125
linux-release-x86_64OK116
macos-release-arm64OK112
macos-release-x86_64OK198
macos-oldrel-arm64OK81
macos-oldrel-x86_64OK246
windows-develOK102
windows-releaseOK88
windows-oldrelOK86
wasm-releaseOK83

Exports:Nmixplot.nmixprint.nmixreadf2ciosdrnisummary.nmix

Dependencies: