Covariance Regression with Random Forests ('CovRegRF') is a random forest method for estimating the covariance matrix of a multivariate response given a set of covariates. Random forest trees are built with a new splitting rule which is designed to maximize the distance between the sample covariance matrix estimates of the child nodes. The method is described in Alakus et al. (2023) <doi:10.1186/s12859-023-05377-y>. 'CovRegRF' uses 'randomForestSRC' package (Ishwaran and Kogalur, 2022) <https://cran.r-project.org/package=randomForestSRC> by freezing at the version 3.1.0. The custom splitting rule feature is utilised to apply the proposed splitting rule. 'LAPACK' and 'BLAS' libraries are used for matrix decompositions. The 'CovRegRF' package includes the header files 'lapacke.h' and 'cblas.h' from the 'LAPACK' and 'BLAS' libraries. The 'LAPACK' library is licensed under modified BSD license.
| Version: | 1.0.4 |
| Depends: | R (≥ 3.6.0) |
| Imports: | data.table, data.tree, DiagrammeR |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: | 2023-09-22 |
| Author: | Cansu Alakus [aut, cre], Denis Larocque [aut], Aurelie Labbe [aut], Hemant Ishwaran [ctb] (Author of included 'randomForestSRC' codes), Udaya B. Kogalur [ctb] (Author of included 'randomForestSRC' codes), Intel Corporation [cph] (Copyright holder of included LAPACKE codes), Keita Teranishi [ctb] (Author of included cblas_dgemm.c codes) |
| Maintainer: | Cansu Alakus <cansu.alakus at hec.ca> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | CovRegRF results |
| Reference manual: | CovRegRF.pdf |
| Vignettes: |
CovRegRF: Covariance Regression with Random Forests |
| Package source: | CovRegRF_1.0.4.tar.gz |
| Windows binaries: | r-devel: CovRegRF_1.0.4.zip, r-release: CovRegRF_1.0.4.zip, r-oldrel: CovRegRF_1.0.4.zip |
| macOS binaries: | r-release (arm64): CovRegRF_1.0.4.tgz, r-oldrel (arm64): CovRegRF_1.0.4.tgz, r-release (x86_64): CovRegRF_1.0.4.tgz, r-oldrel (x86_64): CovRegRF_1.0.4.tgz |
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