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MCCM (version 0.1.0)

Mixed Correlation Coefficient Matrix

Description

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) ; Ben Liu and Peng Zhang (2024) .

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Version

Install

install.packages('MCCM')

Monthly Downloads

197

Version

0.1.0

License

GPL

Maintainer

Ben Liu

Last Published

April 18th, 2024

Functions in MCCM (0.1.0)

mb

Mean Bias
gen_mixed

Continuous and Ordinal Simulated Data
est_mixedGMM

Estimating Mixed Correlation Matrix by IGMM
draw_correlation_matrix

Draw the Correlation Matrix
Phixy

Scaled Bivariate Normal Approximation
esti_polyserial

Polyserial Correlation
MCCM_est

General Function to Estimate Mixed Correlation Coefficient Matrix
mrb

Mean Relative Bias
dphixy

Scaled Bivariate Normal Density
esti_polychoric

Polychoric Correlation
CECERS

Chinese Early Childhood Environment Rating Scale
est_thre

Thresholds Estimation
Parenteral_nutrition

Parenteral_nutrition
gen_CCM

Positive Semidefinite Correlation Matrix
rmse

Root Mean Squared Error
gen_rho

Generate Specific Binormal Distribution
summary_MCCM_est

Summary a MCCM Estimation Result
gen_polyseries

Generate Polyseries Sample
gen_polychoric

Generate Polychoric Sample