R/RcppExports.R

In hheiling/glmmPen: High Dimensional Penalized Generalized Linear Mixed Models (pGLMM)

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

grp_CD_XZ_FA_step <- function(y, X, Z, group, pBigMat, J_f, dims, beta, offset, step_size, sig_g, family, link, init, phi, X_group, K, penalty, params, trace) {
    .Call('_glmmPen_grp_CD_XZ_FA_step', PACKAGE = 'glmmPen', y, X, Z, group, pBigMat, J_f, dims, beta, offset, step_size, sig_g, family, link, init, phi, X_group, K, penalty, params, trace)
}

grp_CD_XZ_step <- function(y, X, Z, group, pBigMat, J_q, dims, beta, offset, step_size, sig_g, family, link, init, phi, XZ_group, K, penalty, params, trace) {
    .Call('_glmmPen_grp_CD_XZ_step', PACKAGE = 'glmmPen', y, X, Z, group, pBigMat, J_q, dims, beta, offset, step_size, sig_g, family, link, init, phi, XZ_group, K, penalty, params, trace)
}

maxprod <- function(X_, y_, v_, m_, n, p) {
    .Call('_glmmPen_maxprod', PACKAGE = 'glmmPen', X_, y_, v_, m_, n, p)
}

soft_thresh <- function(zeta, lambda) {
    .Call('_glmmPen_soft_thresh', PACKAGE = 'glmmPen', zeta, lambda)
}

MCP_soln <- function(zeta, nu, lambda, gamma, alpha) {
    .Call('_glmmPen_MCP_soln', PACKAGE = 'glmmPen', zeta, nu, lambda, gamma, alpha)
}

SCAD_soln <- function(zeta, nu, lambda, gamma, alpha) {
    .Call('_glmmPen_SCAD_soln', PACKAGE = 'glmmPen', zeta, nu, lambda, gamma, alpha)
}

pglm_fit <- function(y, X, dims, beta, offset, family, link, penalty, params, penalty_factor, trace) {
    .Call('_glmmPen_pglm_fit', PACKAGE = 'glmmPen', y, X, dims, beta, offset, family, link, penalty, params, penalty_factor, trace)
}

sample_mc_inner_gibbs <- function(f, z, y, t, NMC, u0, family, link, phi, sig_g) {
    .Call('_glmmPen_sample_mc_inner_gibbs', PACKAGE = 'glmmPen', f, z, y, t, NMC, u0, family, link, phi, sig_g)
}

sample_mc_gibbs_adapt_rw <- function(f, z, y, NMC, u0, proposal_SD, batch, batch_length, offset, nMC_burnin, family, link, phi, sig_g) {
    .Call('_glmmPen_sample_mc_gibbs_adapt_rw', PACKAGE = 'glmmPen', f, z, y, NMC, u0, proposal_SD, batch, batch_length, offset, nMC_burnin, family, link, phi, sig_g)
}

Qfun_FA <- function(y, X, Z, pBigMat, group, J_f, beta, offset, dims, family, link, sig_g, phi) {
    .Call('_glmmPen_Qfun_FA', PACKAGE = 'glmmPen', y, X, Z, pBigMat, group, J_f, beta, offset, dims, family, link, sig_g, phi)
}

sig_gaus_FA <- function(y, X, Z, pBigMat, group, J_q, beta, offset, dims, link) {
    .Call('_glmmPen_sig_gaus_FA', PACKAGE = 'glmmPen', y, X, Z, pBigMat, group, J_q, beta, offset, dims, link)
}

invlink <- function(link, eta) {
    .Call('_glmmPen_invlink', PACKAGE = 'glmmPen', link, eta)
}

Qfun <- function(y, X, Z, pBigMat, group, J_q, beta, offset, dims, family, link, sig_g, phi) {
    .Call('_glmmPen_Qfun', PACKAGE = 'glmmPen', y, X, Z, pBigMat, group, J_q, beta, offset, dims, family, link, sig_g, phi)
}

sig_gaus <- function(y, X, Z, pBigMat, group, J_q, beta, offset, dims, link) {
    .Call('_glmmPen_sig_gaus', PACKAGE = 'glmmPen', y, X, Z, pBigMat, group, J_q, beta, offset, dims, link)
}

phi_ml <- function(y, eta, link, limit, eps, phi) {
    .Call('_glmmPen_phi_ml', PACKAGE = 'glmmPen', y, eta, link, limit, eps, phi)
}

phi_ml_init <- function(y, eta, link, limit, eps) {
    .Call('_glmmPen_phi_ml_init', PACKAGE = 'glmmPen', y, eta, link, limit, eps)
}

#' @importFrom RcppParallel RcppParallelLibs
NULL

Qfun_quad_beta <- function(Q0, step_size, diff0, eta, eta0, beta, beta0) {
    .Call('_glmmPen_Qfun_quad_beta', PACKAGE = 'glmmPen', Q0, step_size, diff0, eta, eta0, beta, beta0)
}