Implementations of various robust and flexible model-based clustering methods for data sets with missing values at random (Tong and Tortora, 2025, <doi:10.18637/jss.v115.i03>). Two main models are: Multivariate Contaminated Normal Mixture (MCNM, Tong and Tortora, 2022, <doi:10.1007/s11634-021-00476-1>) and Multivariate Generalized Hyperbolic Mixture (MGHM, Wei et al., 2019, <doi:10.1016/j.csda.2018.08.016>). Mixtures via some special or limiting cases of the multivariate generalized hyperbolic distribution are also included: Normal-Inverse Gaussian, Symmetric Normal-Inverse Gaussian, Skew-Cauchy, Cauchy, Skew-t, Student's t, Normal, Symmetric Generalized Hyperbolic, Hyperbolic Univariate Marginals, Hyperbolic, and Symmetric Hyperbolic. Funding: This work was partially supported by the National Science foundation NSF Grant NO. 2209974.
| Version: | 3.0.6 |
| Depends: | R (≥ 3.5.0) |
| Imports: | mvtnorm (≥ 1.1-2), mnormt (≥ 2.0.2), cluster (≥ 2.1.2), MASS (≥ 7.3), numDeriv (≥ 8.1.1), Bessel (≥ 0.6.0), mclust (≥ 5.0.0), mice (≥ 3.10.0) |
| Published: | 2026-01-14 |
| DOI: | 10.32614/CRAN.package.MixtureMissing |
| Author: | Hung Tong [aut, cre], Cristina Tortora [aut, ths, dgs] |
| Maintainer: | Hung Tong <hungtongmx at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Citation: | MixtureMissing citation info |
| In views: | Cluster, MissingData |
| CRAN checks: | MixtureMissing results |
| Reference manual: | MixtureMissing.html , MixtureMissing.pdf |
| Package source: | MixtureMissing_3.0.6.tar.gz |
| Windows binaries: | r-devel: MixtureMissing_3.0.6.zip, r-release: MixtureMissing_3.0.6.zip, r-oldrel: MixtureMissing_3.0.6.zip |
| macOS binaries: | r-release (arm64): MixtureMissing_3.0.6.tgz, r-oldrel (arm64): MixtureMissing_3.0.6.tgz, r-release (x86_64): MixtureMissing_3.0.6.tgz, r-oldrel (x86_64): MixtureMissing_3.0.6.tgz |
| Old sources: | MixtureMissing archive |
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