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-4.4-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'))

Peer review:

Datasets:

On CRAN:

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

17 exports 0.09 score 11 dependencies 161 downloads

Last updated 5 months agofrom:14f74004d6. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 17 2024
R-4.5-winOKSep 17 2024
R-4.5-linuxOKSep 17 2024
R-4.4-winOKSep 17 2024
R-4.4-macOKSep 17 2024
R-4.3-winOKSep 17 2024
R-4.3-macOKSep 17 2024

Exports:dphixydraw_correlation_matrixest_mixedGMMest_threesti_polychoricesti_polyserialgen_CCMgen_mixedgen_polychoricgen_polyseriesgen_rhombMCCM_estmrbPhixyrmsesummary_MCCM_est

Dependencies:admisclatticelavaanMASSMatrixmnormtmvtnormnumDerivpbivnormpolycorquadprog