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MixSemiRob: Mixture Models: Parametric, Semiparametric, and Robust

Various functions are provided to estimate parametric mixture models (with Gaussian, t, Laplace, log-concave distributions, etc.) and non-parametric mixture models. The package performs hypothesis tests and addresses label switching issues in mixture models. The package also allows for parameter estimation in mixture of regressions, proportion-varying mixture of regressions, and robust mixture of regressions.

Version: 1.1.0
Depends: R (≥ 2.10)
Imports: GoFKernel, MASS, mixtools, mvtnorm, Rlab, robustbase, ucminf, pracma, quadprog, stats
Suggests: knitr, rmarkdown
Published: 2023-09-20
Author: Suyeon Kang ORCID iD [aut, cre], Xin Shen ORCID iD [aut], Weixin Yao ORCID iD [aut], Sijia Xiang [aut], Yan Ge [aut, trl]
Maintainer: Suyeon Kang <suyeon.kang at ufl.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: MixSemiRob results

Documentation:

Reference manual: MixSemiRob.pdf

Downloads:

Package source: MixSemiRob_1.1.0.tar.gz
Windows binaries: r-devel: MixSemiRob_1.1.0.zip, r-release: MixSemiRob_1.1.0.zip, r-oldrel: MixSemiRob_1.1.0.zip
macOS binaries: r-release (arm64): MixSemiRob_1.1.0.tgz, r-oldrel (arm64): MixSemiRob_1.1.0.tgz, r-release (x86_64): MixSemiRob_1.1.0.tgz, r-oldrel (x86_64): MixSemiRob_1.1.0.tgz
Old sources: MixSemiRob archive

Linking:

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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.
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