R/RcppExports.R

In emBayes: Robust Bayesian Variable Selection via Expectation-Maximization

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

EMR <- function(y, X, C, n, p, q, alpha, beta, sigma2, theta, Pgamma, invS) {
    .Call(`_emBayes_EMR`, y, X, C, n, p, q, alpha, beta, sigma2, theta, Pgamma, invS)
}

EMQR <- function(y, X, C, n, p, q, quant, alpha, beta, sigma, theta, s0, s1, Pgamma, invS, ep1, ep22, vn, vp) {
    .Call(`_emBayes_EMQR`, y, X, C, n, p, q, quant, alpha, beta, sigma, theta, s0, s1, Pgamma, invS, ep1, ep22, vn, vp)
}

EMVCR <- function(y, X, C, W, r, rs, n, m, nt, ns, p, q, alpha, beta, g, gn, phi2, sigma2, theta, Pgamma, S) {
    .Call(`_emBayes_EMVCR`, y, X, C, W, r, rs, n, m, nt, ns, p, q, alpha, beta, g, gn, phi2, sigma2, theta, Pgamma, S)
}

EMVCQR <- function(y, X, C, W, r, rs, n, m, nt, ns, p, q, quant, alpha, beta, g, gn, phi2, sigma, theta, Pgamma, S, ep1, ep22, vn, vp) {
    .Call(`_emBayes_EMVCQR`, y, X, C, W, r, rs, n, m, nt, ns, p, q, quant, alpha, beta, g, gn, phi2, sigma, theta, Pgamma, S, ep1, ep22, vn, vp)
}

logR <- function(y, X, C, alpha, beta, sigma2, theta, s0, s1) {
    .Call(`_emBayes_logR`, y, X, C, alpha, beta, sigma2, theta, s0, s1)
}

logQR <- function(y, X, C, alpha, beta, sigma, theta, s0, s1, ep1, ep22) {
    .Call(`_emBayes_logQR`, y, X, C, alpha, beta, sigma, theta, s0, s1, ep1, ep22)
}

logVCR <- function(y, X, C, W, r, rs, n, m, ns, alpha, beta, g, gn, phi2, sigma2, theta, s0, s1) {
    .Call(`_emBayes_logVCR`, y, X, C, W, r, rs, n, m, ns, alpha, beta, g, gn, phi2, sigma2, theta, s0, s1)
}

logVCQR <- function(y, X, C, W, r, rs, n, m, ns, alpha, beta, g, gn, phi2, sigma, theta, s0, s1, ep1, ep22) {
    .Call(`_emBayes_logVCQR`, y, X, C, W, r, rs, n, m, ns, alpha, beta, g, gn, phi2, sigma, theta, s0, s1, ep1, ep22)
}

Soft <- function(z, lambda) {
    .Call(`_emBayes_Soft`, z, lambda)
}