EMMIXmfa
2.0.14Mixture Models with Component-Wise Factor Analyzers
Overview
We provide functions to fit finite mixtures of multivariate normal or t-distributions to data with various factor analytic structures adopted for the covariance/scale matrices. The factor analytic structures available include mixtures of factor analyzers and mixtures of common factor analyzers. The latter approach is so termed because the matrix of factor loadings is common to components before the component-specific rotation of the component factors to make them white noise. Note that the component-factor loadings are not common after this rotation. Maximum likelihood estimators of model parameters are obtained via the Expectation-Maximization algorithm. See descriptions of the algorithms used in McLachlan GJ, Peel D (2000) doi:10.1002/0471721182.ch8 McLachlan GJ, Peel D (2000) <ISBN:1-55860-707-2> McLachlan GJ, Peel D, Bean RW (2003) doi:10.1016/S0167-9473(02)00183-4 McLachlan GJ, Bean RW, Ben-Tovim Jones L (2007) doi:10.1016/j.csda.2006.09.015 Baek J, McLachlan GJ, Flack LK (2010) doi:10.1109/TPAMI.2009.149 Baek J, McLachlan GJ (2011) doi:10.1093/bioinformatics/btr112 McLachlan GJ, Baek J, Rathnayake SI (2011) doi:10.1002/9781119995678.ch9.
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- Examples that run
- 73%
- Documented parameters
- 96%
- Return-value docs
- 88%
- References docs
- 64%
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3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 2.0.14Latest
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 2.0.112019-12-16 · diff ↗
- RR 3.6.0 released · 2019-04-26
- 2.0.72018-10-19
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2018-10-19
- Total releases
- 3 / 8 yrs
- License
- GPL (>= 2) OSI
- Download size
- 31 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet