Provides sampling and density functions for matrix variate normal, t, and inverted t distributions; ML estimation for matrix variate normal and t distributions using the EM algorithm, including some restrictions on the parameters; and classification by linear and quadratic discriminant analysis for matrix variate normal and t distributions described in Thompson et al. (2019) <arXiv:1907.09565>. Performs clustering with matrix variate normal and t mixture models.
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Summary
Provides sampling and density functions for matrix variate normal, t, and inverted t distributions; ML estimation for matrix variate normal and t distributions using the EM algorithm, including some restrictions on the parameters; and classification by linear and quadratic discriminant analysis for matrix variate normal and t distributions described in Thompson et al. (2019) <arXiv:1907.09565>. Performs clustering with matrix variate normal and t mixture models.
Last Updated
Dec 13, 2019 at 20:37
License
GPL-3
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6
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