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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 |
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 |
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 |
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 |
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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.