Computing the Singular BIC for Multiple Models [R package sBIC version 0.2.0]

Luca Weihs

sBIC: Computing the Singular BIC for Multiple Models

Computes the sBIC for various singular model collections including: binomial mixtures, factor analysis models, Gaussian mixtures, latent forests, latent class analyses, and reduced rank regressions.

Version: 0.2.0

Imports: poLCA, R.oo (≥ 1.20.0), R.methodsS3, mclust, igraph (≥ 1.0.1), Rcpp (≥ 0.12.3), combinat, flexmix, hash

LinkingTo: Rcpp

Suggests: testthat, mvtnorm, knitr, MASS

Published: 2016年10月01日

DOI: 10.32614/CRAN.package.sBIC

Author: Luca Weihs [aut, cre], Martyn Plummer [ctb]

Maintainer: Luca Weihs <lucaw at uw.edu>

BugReports: https://github.com/Lucaweihs/sBIC/issues

License: GPL (≥ 3)

URL: https://github.com/Lucaweihs/sBIC

NeedsCompilation: yes

Materials: README

CRAN checks: sBIC results

Documentation:

Reference manual: sBIC.html , sBIC.pdf

Vignettes: Binomial Mixtures (source, R code)
Factor Analysis (source, R code)
Gaussian Mixtures (source, R code)
Latent Class Analysis (source, R code)
Reduced Rank Regression (source, R code)
Introduction to sBIC (source, R code)

Downloads:

Package source: sBIC_0.2.0.tar.gz

Windows binaries: r-devel: sBIC_0.2.0.zip, r-release: sBIC_0.2.0.zip, r-oldrel: sBIC_0.2.0.zip

macOS binaries: r-release (arm64): sBIC_0.2.0.tgz, r-oldrel (arm64): sBIC_0.2.0.tgz, r-release (x86_64): sBIC_0.2.0.tgz, r-oldrel (x86_64): sBIC_0.2.0.tgz

Linking:

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