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Implements parsimonious mixtures of MSEN and MTIN distributions via expectation- maximization based algorithms for model-based clustering. For each mixture component, parsimony is reached via the eigen-decomposition of the scale matrices and by imposing a constraint on the tailedness parameter. This produces a family of 28 parsimonious mixture models for each distribution.
| Version: | 1.0.0 |
| Depends: | R (≥ 2.10) |
| Imports: | doSNOW, foreach, snow, TSdist, tidyr, data.table, expint, zipfR, mclust, rlist, withr |
| Published: | 2021-10-20 |
| DOI: | 10.32614/CRAN.package.SenTinMixt |
| Author: | Salvatore D. Tomarchio [aut, cre], Bagnato Luca [aut], Antonio Punzo [aut] |
| Maintainer: | Salvatore D. Tomarchio <daniele.tomarchio at unict.it> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| CRAN checks: | SenTinMixt results |
| Reference manual: | SenTinMixt.pdf |
| Package source: | SenTinMixt_1.0.0.tar.gz |
| Windows binaries: | r-devel: SenTinMixt_1.0.0.zip, r-release: SenTinMixt_1.0.0.zip, r-oldrel: SenTinMixt_1.0.0.zip |
| macOS binaries: | r-release (arm64): SenTinMixt_1.0.0.tgz, r-oldrel (arm64): SenTinMixt_1.0.0.tgz, r-release (x86_64): SenTinMixt_1.0.0.tgz, r-oldrel (x86_64): SenTinMixt_1.0.0.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.