MixMatrix: Classification with Matrix Variate Normal and t Distributions
In MixMatrix: 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.
MixMatrix documentation built on Nov. 16, 2021, 9:25 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.