MixMatrix-package: Classification with Matrix Variate Normal and t Distributions

In MixMatrix: Classification with Matrix Variate Normal and t Distributions

Classification with Matrix Variate Normal and t Distributions

Description

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). Performs clustering with matrix variate normal and t mixture models.

Author(s)

Maintainer: Geoffrey Thompson [e-mail] (ORCID)

Other contributors:

• B. D. Ripley [e-mail] (author of original lda and qda functions) [contributor, copyright holder]

• W. N. Venables (author of original lda and qda functions) [contributor, copyright holder]

See Also

Useful links:

• https://github.com/gzt/MixMatrix/

• https://gzt.github.io/MixMatrix/

• Report bugs at https://github.com/gzt/MixMatrix/issues

MixMatrix documentation built on Oct. 1, 2024, 1:07 a.m.