Package: jointMeanCov 0.1.0

jointMeanCov: Joint Mean and Covariance Estimation for Matrix-Variate Data

Jointly estimates two-group means and covariances for matrix-variate data and calculates test statistics. This package implements the algorithms defined in Hornstein, Fan, Shedden, and Zhou (2018) <doi:10.1080/01621459.2018.1429275>.

Authors:Michael Hornstein [aut, cre], Roger Fan [aut], Kerby Shedden [aut], Shuheng Zhou [aut]

jointMeanCov_0.1.0.tar.gz
jointMeanCov_0.1.0.zip(r-4.7)jointMeanCov_0.1.0.zip(r-4.6)jointMeanCov_0.1.0.zip(r-4.5)
jointMeanCov_0.1.0.tgz(r-4.6-any)jointMeanCov_0.1.0.tgz(r-4.5-any)
jointMeanCov_0.1.0.tar.gz(r-4.7-any)jointMeanCov_0.1.0.tar.gz(r-4.6-any)
jointMeanCov_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
jointMeanCov/json (API)

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

On CRAN:

Conda:

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

1.00 score 5 scripts 174 downloads 7 exports 1 dependencies

Last updated from:25d6dd573a. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK116
source / vignettesOK167
linux-release-x86_64OK117
macos-release-arm64OK204
macos-oldrel-arm64OK154
windows-develOK73
windows-releaseOK106
windows-oldrelOK68
wasm-releaseOK95

Exports:GeminiBGeminiBPathjointMeanCovGroupCenjointMeanCovModSelCenjointMeanCovStabilitytheoryRowpenUpperBoundtheoryRowpenUpperBoundDiagA

Dependencies:glasso