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: 2016-10-01
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

Downloads:

Reference manual: sBIC.pdf
Vignettes: Binomial Mixtures
Factor Analysis
Gaussian Mixtures
Latent Class Analysis
Reduced Rank Regression
Introduction to sBIC
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
OS X Mavericks binaries: r-release: sBIC_0.2.0.tgz, r-oldrel: sBIC_0.2.0.tgz

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