esti_polychoric {MCCM}

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))