esti_polychoric: Polychoric Correlation

In MCCM: Mixed Correlation Coefficient Matrix

Polychoric Correlation

Description

Estimate the polychoric correlation coefficient.

Usage

esti_polychoric(X, maxn = 100, e = 1e-08, ct = FALSE)

Arguments

X	a matrix(2*N) or dataframe contains two polychoric variable, or a contingency table with both columns and rows names.
maxn	the maximum iterations times.
e	the maximum tolerance of convergence.
ct	TRUE for contingency table, FALSE for matrix or dataframe

Value

rho	estimated value of polychoric correlation coefficient.
std	standard deviation of rho.
iter	times of iteration convergence.
Ex, Ey	the support points series of regression model

References

Zhang, P., Liu, B., & Pan, J. (2024). Iteratively Reweighted Least Squares Method for Estimating Polyserial and Polychoric Correlation Coefficients. Journal of Computational and Graphical Statistics, 33(1), 316–328. https://doi.org/10.1080/10618600.2023.2257251

See Also

esti_polyserial

Examples

X = gen_polychoric(1000,0.5,0:1,-1:0)
result = esti_polychoric(X)
print(c(result$rho,result$std,result$iter))

MCCM documentation built on May 29, 2024, 12:09 p.m.