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-4.5)MCCM_0.1.0.zip(r-4.4)MCCM_0.1.0.zip(r-4.3)
MCCM_0.1.0.tgz(r-4.5-any)MCCM_0.1.0.tgz(r-4.4-any)MCCM_0.1.0.tgz(r-4.3-any)
MCCM_0.1.0.tar.gz(r-4.5-noble)MCCM_0.1.0.tar.gz(r-4.4-noble)
MCCM_0.1.0.tgz(r-4.4-emscripten)MCCM_0.1.0.tgz(r-4.3-emscripten)
MCCM.pdf |MCCM.html
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 149 downloads 17 exports 11 dependencies

Last updated 12 months agofrom:14f74004d6. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 16 2025
R-4.5-winOKMar 16 2025
R-4.5-macOKMar 16 2025
R-4.5-linuxOKMar 16 2025
R-4.4-winOKMar 16 2025
R-4.4-macOKMar 16 2025
R-4.4-linuxOKMar 16 2025
R-4.3-winOKMar 16 2025
R-4.3-macOKMar 16 2025

Exports:dphixydraw_correlation_matrixest_mixedGMMest_threesti_polychoricesti_polyserialgen_CCMgen_mixedgen_polychoricgen_polyseriesgen_rhombMCCM_estmrbPhixyrmsesummary_MCCM_est

Dependencies:admisclatticelavaanMASSMatrixmnormtmvtnormnumDerivpbivnormpolycorquadprog