R/RcppExports.R

In GPCMlasso: Differential Item Functioning in Generalized Partial Credit Models

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

loglikPCMlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
    .Call(`_GPCMlasso_loglikPCMlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
}

scorePCMlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
    .Call(`_GPCMlasso_scorePCMlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
}

loglikDIFlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
    .Call(`_GPCMlasso_loglikDIFlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
}

scoreDIFlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
    .Call(`_GPCMlasso_scoreDIFlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
}

loglikscorePCMlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
    .Call(`_GPCMlasso_loglikscorePCMlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
}

loglikscoreDIFlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
    .Call(`_GPCMlasso_loglikscoreDIFlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
}