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Implements finite mixtures of matrix-variate contaminated normal distributions via expectation conditional-maximization algorithm for model-based clustering, as described in Tomarchio et al.(2020) <doi:10.48550/arXiv.2005.03861>. One key advantage of this model is the ability to automatically detect potential outlying matrices by computing their a posteriori probability of being typical or atypical points. Finite mixtures of matrix-variate t and matrix-variate normal distributions are also implemented by using expectation-maximization algorithms.
| Version: | 1.0.0 |
| Depends: | R (≥ 2.10) |
| Imports: | doSNOW, foreach, snow, withr |
| Published: | 2021-06-11 |
| DOI: | 10.32614/CRAN.package.MatrixMixtures |
| Author: | Salvatore D. Tomarchio [aut], Michael P.B. Gallaugher [aut, cre], Antonio Punzo [aut], Paul D. McNicholas [aut] |
| Maintainer: | Michael P.B. Gallaugher <michael_gallaugher at baylor.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | MatrixMixtures results |
| Reference manual: | MatrixMixtures.pdf |
| Package source: | MatrixMixtures_1.0.0.tar.gz |
| Windows binaries: | r-devel: MatrixMixtures_1.0.0.zip, r-release: MatrixMixtures_1.0.0.zip, r-oldrel: MatrixMixtures_1.0.0.zip |
| macOS binaries: | r-release (arm64): MatrixMixtures_1.0.0.tgz, r-oldrel (arm64): MatrixMixtures_1.0.0.tgz, r-release (x86_64): MatrixMixtures_1.0.0.tgz, r-oldrel (x86_64): MatrixMixtures_1.0.0.tgz |
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