Package: MCCM 0.1.0

MCCM: Mixed Correlation Coefficient Matrix

The IRLS (Iteratively Reweighted Least Squares) and GMM (Generalized Method of Moments) methods are applied to estimate mixed correlation coefficient matrix (Pearson, Polyseries, Polychoric), which can be estimated in pairs or simultaneously. For more information see Peng Zhang and Ben Liu (2024) <doi:10.1080/10618600.2023.2257251>; Ben Liu and Peng Zhang (2024) <doi:10.48550/arXiv.2404.06781>.

Authors:Ben Liu [aut, cre], Peng Zhang [ths], Xiaowei Lou [aut, dtc]

MCCM_0.1.0.tar.gz
MCCM_0.1.0.zip(r-4.7-any)MCCM_0.1.0.zip(r-4.6-any)MCCM_0.1.0.zip(r-4.5-any)
MCCM_0.1.0.tgz(r-4.6-any)MCCM_0.1.0.tgz(r-4.5-any)
MCCM_0.1.0.tar.gz(r-4.7-any)MCCM_0.1.0.tar.gz(r-4.6-any)
MCCM_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
MCCM/json (API)

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

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 203 downloads 17 exports 11 dependencies

Last updated from:14f74004d6. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK105
source / vignettesOK176
linux-releaseOK97
macos-releaseOK163
macos-oldrelOK180
windows-develOK93
windows-releaseOK59
windows-oldrelOK83
wasm-releaseOK82

Exports:dphixydraw_correlation_matrixest_mixedGMMest_threesti_polychoricesti_polyserialgen_CCMgen_mixedgen_polychoricgen_polyseriesgen_rhombMCCM_estmrbPhixyrmsesummary_MCCM_est

Dependencies:admisclatticelavaanMASSMatrixmnormtmvtnormnumDerivpbivnormpolycorquadprog