Package: CovRegRF 2.0.1

Cansu Alakus

CovRegRF: Covariance Regression with Random Forests

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. The 'randomForestSRC' package implements 'OpenMP' by default, contingent upon the support provided by the target architecture and operating system. In this package, 'LAPACK' and 'BLAS' libraries are used for matrix decompositions.

Authors:Cansu Alakus [aut, cre], Denis Larocque [aut], Aurelie Labbe [aut], Hemant Ishwaran [ctb], Udaya B. Kogalur [ctb], Intel Corporation [cph], Keita Teranishi [ctb]

CovRegRF_2.0.1.tar.gz
CovRegRF_2.0.1.tar.gz(r-4.5-noble)CovRegRF_2.0.1.tar.gz(r-4.4-noble)
CovRegRF_2.0.1.tgz(r-4.4-emscripten)CovRegRF_2.0.1.tgz(r-4.3-emscripten)
CovRegRF.pdf |CovRegRF.html
CovRegRF/json (API)
NEWS

# Install 'CovRegRF' in R:
install.packages('CovRegRF', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • data - Generated example data

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.18 score 3 scripts 294 downloads 8 exports 68 dependencies

Last updated 5 months agofrom:ce3abb83d7. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-linux-x86_64OKNov 13 2024

Exports:covregrfplot.vimpplot.vimp.covregrfpredict.covregrfprint.covregrfsignificance.testvimpvimp.covregrf

Dependencies:base64encbitbit64bslibcachemclicliprcolorspacecpp11crayondata.tabledata.treeDiagrammeRdigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsgluehighrhmshtmltoolshtmlwidgetsigraphjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMatrixmemoisemimemunsellpillarpkgconfigprettyunitsprogresspurrrR6rappdirsRColorBrewerreadrrlangrmarkdownrstudioapisassscalesstringistringrtibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunyaml

CovRegRF: Covariance Regression with Random Forests

Rendered fromCovRegRF.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2024-02-14
Started: 2022-09-22