Package: MixMatrix 0.2.8
MixMatrix: Classification with Matrix Variate Normal and t Distributions
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) <doi:10.1080/10618600.2019.1696208>. Performs clustering with matrix variate normal and t mixture models.
Authors:
MixMatrix_0.2.8.tar.gz
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MixMatrix.pdf |MixMatrix.html✨
MixMatrix/json (API)
NEWS
| # Install 'MixMatrix' in R: |
| install.packages('MixMatrix', repos = c('https://gzt.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gzt/mixmatrix/issues
Last updated 1 months agofrom:2295b55c06. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 30 2024 |
| R-4.5-win-x86_64 | OK | Oct 30 2024 |
| R-4.5-linux-x86_64 | OK | Oct 30 2024 |
| R-4.4-win-x86_64 | OK | Oct 30 2024 |
| R-4.4-mac-x86_64 | OK | Oct 30 2024 |
| R-4.4-mac-aarch64 | OK | Oct 30 2024 |
| R-4.3-win-x86_64 | OK | Oct 30 2024 |
| R-4.3-mac-x86_64 | OK | Oct 30 2024 |
| R-4.3-mac-aarch64 | OK | Oct 30 2024 |
Exports:ARgenerateCSgeneratedmatrixinvtdmatrixnormdmatrixtinit_matrixmixturematrixldamatrixmixturematrixqdaMLmatrixnormMLmatrixtrmatrixinvtrmatrixnormrmatrixt
Dependencies:CholWishartglueRcppRcppArmadillo
Discriminant Analysis for Matrix Variate Distributions
Rendered fromdiscriminant-analysis.Rmdusingknitr::rmarkdownon Oct 30 2024.Last update: 2024-09-30
Started: 2018-02-23
Matrix Variate Normal Distributions with MixMatrix
Rendered frommatrixnormal.Rmdusingknitr::rmarkdownon Oct 30 2024.Last update: 2024-09-30
Started: 2018-02-05
ML estimation of the Matrix Variate t Distribution
Rendered frommatrix-t-estimation.Rmdusingknitr::rmarkdownon Oct 30 2024.Last update: 2024-09-30
Started: 2019-06-22
Matrix Variate Mixture Models with the t distribution
Rendered frommixturemodel.Rmdusingknitr::rmarkdownon Oct 30 2024.Last update: 2024-09-30
Started: 2019-06-29
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Generate a unit AR(1) covariance matrix | ARgenerate |
| Generate a compound symmetric correlation matrix | CSgenerate |
| Initializing settings for Matrix Mixture Models | init_matrixmixture |
| LDA for matrix variate distributions | matrixlda |
| Fit a matrix variate mixture model | matrixmixture |
| Quadratic Discriminant Analysis for Matrix Variate Observations | matrixqda |
| Maximum likelihood estimation for matrix normal distributions | MLmatrixnorm |
| Maximum likelihood estimation for matrix variate t distributions | MLmatrixt |
| Classify Matrix Variate Observations by Linear Discrimination | predict.matrixlda |
| Classify Matrix Variate Observations by Quadratic Discrimination | predict.matrixqda |
| Distribution functions for matrix variate inverted t distributions | dmatrixinvt rmatrixinvt |
| Matrix variate Normal distribution functions | dmatrixnorm rmatrixnorm |
| Distribution functions for the matrix variate t distribution. | dmatrixt rmatrixt |
