R/RcppExports.R

In mDAG: Inferring Causal Network from Mixed Observational Data Using a Directed Acyclic Graph

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

gaussian_cpp <- function() {
    .Call('_mDAG_gaussian_cpp', PACKAGE = 'mDAG')
}

binomial_cpp <- function() {
    .Call('_mDAG_binomial_cpp', PACKAGE = 'mDAG')
}

poisson_cpp <- function() {
    .Call('_mDAG_poisson_cpp', PACKAGE = 'mDAG')
}

glm_fit_cpp <- function(x, y, weights, family) {
    .Call('_mDAG_glm_fit_cpp', PACKAGE = 'mDAG', x, y, weights, family)
}

logLik_cpp <- function(fit, samplesize) {
    .Call('_mDAG_logLik_cpp', PACKAGE = 'mDAG', fit, samplesize)
}

logistf_control_cpp <- function() {
    .Call('_mDAG_logistf_control_cpp', PACKAGE = 'mDAG')
}

logistf_fit_cpp <- function(x, y, weights, control) {
    .Call('_mDAG_logistf_fit_cpp', PACKAGE = 'mDAG', x, y, weights, control)
}

multinom_BIC_cpp <- function(x, y, weights) {
    .Call('_mDAG_multinom_BIC_cpp', PACKAGE = 'mDAG', x, y, weights)
}

ScoreNodeWithNoneParents <- function(type, level, v, data, weights) {
    .Call('_mDAG_ScoreNodeWithNoneParents', PACKAGE = 'mDAG', type, level, v, data, weights)
}

InitScore <- function(type, level, data, weights) {
    .Call('_mDAG_InitScore', PACKAGE = 'mDAG', type, level, data, weights)
}

ReturnParents <- function(i, AdjMat) {
    .Call('_mDAG_ReturnParents', PACKAGE = 'mDAG', i, AdjMat)
}

subcolMatrix <- function(matrix, index) {
    .Call('_mDAG_subcolMatrix', PACKAGE = 'mDAG', matrix, index)
}

ScoreGraph <- function(type, level, data, weights, AdjMat) {
    .Call('_mDAG_ScoreGraph', PACKAGE = 'mDAG', type, level, data, weights, AdjMat)
}

SettingEdges <- function(scores, data, rst, type, level, SNP, weights) {
    .Call('_mDAG_SettingEdges', PACKAGE = 'mDAG', scores, data, rst, type, level, SNP, weights)
}

AddReverseDelete <- function(AdjMat, scores, data, rst, type, level, SNP, weights) {
    invisible(.Call('_mDAG_AddReverseDelete', PACKAGE = 'mDAG', AdjMat, scores, data, rst, type, level, SNP, weights))
}

GreedySearch <- function(data, type, level, SNP, rst, weights) {
    .Call('_mDAG_GreedySearch', PACKAGE = 'mDAG', data, type, level, SNP, rst, weights)
}