CRAN/E | CovRegRF

CovRegRF

Covariance Regression with Random Forests

Installation

About

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) 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.

Key Metrics

Version 1.0.5
R ≥ 3.6.0
Published 2023-12-07 132 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks CovRegRF results

Downloads

Yesterday 2
Last 7 days 36 -49%
Last 30 days 239 -30%
Last 90 days 812 -9%
Last 365 days 3.126 +69%

Maintainer

Maintainer

Cansu Alakus

cansu.alakus@hec.ca

Authors

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)

Material

README
NEWS
Reference manual
Package source

Vignettes

CovRegRF: Covariance Regression with Random Forests

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

CovRegRF archive

Depends

R ≥ 3.6.0

Imports

data.table
data.tree
DiagrammeR

Suggests

knitr
rmarkdown
testthat ≥ 3.0.0