mixSPE: Mixtures of Power Exponential and Skew Power Exponential Distributions for Use in Model-Based Clustering and Classification

Mixtures of skewed and elliptical distributions are implemented using mixtures of multivariate skew power exponential and power exponential distributions, respectively. A generalized expectation-maximization framework is used for parameter estimation. Methodology for mixtures of power exponential distributions is from Dang et al. (2015) <doi:10.1111/biom.12351>.

Version: 0.9.1
Imports: mvtnorm
Suggests: testthat
Published: 2021-01-25
Author: Ryan P. Browne[aut, cre], Utkarsh J. Dang[aut, cre], Michael P. B. Gallaugher[ctb], and Paul D. McNicholas[aut]
Maintainer: Utkarsh J. Dang <udang at binghamton.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
In views: Distributions
CRAN checks: mixSPE results


Reference manual: mixSPE.pdf


Package source: mixSPE_0.9.1.tar.gz
Windows binaries: r-devel: mixSPE_0.9.1.zip, r-release: mixSPE_0.9.1.zip, r-oldrel: mixSPE_0.9.1.zip
macOS binaries: r-release (arm64): mixSPE_0.9.1.tgz, r-oldrel (arm64): mixSPE_0.9.1.tgz, r-release (x86_64): mixSPE_0.9.1.tgz, r-oldrel (x86_64): mixSPE_0.9.1.tgz
Old sources: mixSPE archive


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