R/RcppExports.R

In metacart: Meta-CART: A Flexible Approach to Identify Moderators in Meta-Analysis

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

#' Compute tau2 
#' 
#' @param x1 the effect size g in the unsplit leaves
#' @param x2 the sampling variance vi in the unsplit leaves
#' @param x3 the lable of the unsplit leaves
#' @param x4 the sorted effect size in the parent leaf
#' @param x5 the sorted sampling variance in the parent leaf
#' @param xuni the unique labels in the unsplit leaves
#' @keywords internal
.compute_tau_ <- function(x1, x2, x3, xuni, x4, x5) {
    .Call('_metacart_compute_tau_', PACKAGE = 'metacart', x1, x2, x3, xuni, x4, x5)
}

compute_left_ <- function(x1, x2, x3, xuni) {
    .Call('_metacart_compute_left_', PACKAGE = 'metacart', x1, x2, x3, xuni)
}

#' Compute re Q for different values of tau2
#' 
#' @param x1 the effect size g in the unsplit leaves
#' @param x2 the sampling variance vi in the unsplit leaves
#' @param x3 the labels of nodes in the unsplit leaves
#' @param x4 tau2
#' @param x5 the effect size g in the parent leaf
#' @param x6 the sampling variance vi in the parent leaf
#' @param xuni the unique labels in the unsplit leaves
#' @keywords internal
.compute_re_Q_ <- function(x1, x2, x3, x4, xuni, x5, x6) {
    .Call('_metacart_compute_re_Q_', PACKAGE = 'metacart', x1, x2, x3, x4, xuni, x5, x6)
}

complexity_decrease_ <- function(inNode, delQ, pnode) {
    .Call('_metacart_complexity_decrease_', PACKAGE = 'metacart', inNode, delQ, pnode)
}

find_offsprings_ <- function(nodeID, allNodes) {
    .Call('_metacart_find_offsprings_', PACKAGE = 'metacart', nodeID, allNodes)
}

find_children_vec <- function(nodeIDv, allNodes) {
    .Call('_metacart_find_children_vec', PACKAGE = 'metacart', nodeIDv, allNodes)
}

find_ancestor_ <- function(nodeID) {
    .Call('_metacart_find_ancestor_', PACKAGE = 'metacart', nodeID)
}

#' Partition the test set based on a trained tree
#' 
#' @param x1 the tree component of the REmrt object
#' @param x2 the moderators in the test set
#' @param x3 indicates whether a moderator is numeric or not
#' @param x4 the index vector of the spliting moderators
#' @param x5 the list of split points
#' @param x6 the moderators in the training set
#' @keywords internal
.partition <- function(x1, x2, x3, x4, x5, x6) {
    .Call('_metacart_partition', PACKAGE = 'metacart', x1, x2, x3, x4, x5, x6)
}

rcpp_hello_world <- function() {
    .Call('_metacart_rcpp_hello_world', PACKAGE = 'metacart')
}

#' Compute the subgroup effect sizes
#' 
#' @param x1 the node labels for each study
#' @param y  the effect size
#' @param vi the sampling variance
#' @param tau2 the residual heterogeneity
#' @keywords internal
.ComputeY <- function(x1, y, vi, tau2) {
    .Call('_metacart_ComputeY', PACKAGE = 'metacart', x1, y, vi, tau2)
}

#' Predict effect size for the test set
#' 
#' @param x1 the list of subgroup means
#' @param x2 predicted subgroup membership for the test set
#' @keywords internal
.PredY <- function(x1, x2) {
    .Call('_metacart_PredY', PACKAGE = 'metacart', x1, x2)
}

#' Replace missing values by the overall weighted mean
#' 
#' @param x1 the two-column matrix of the indices of missing values
#' @param x2 the matrix of predicted y with missing values
#' @param y  the effect size
#' @param vi the sampling variance
#' @param tau2 the residual heterogeneity
#' @keywords internal
.ReplaceNA <- function(x1, x2, y, vi, tau2) {
    .Call('_metacart_ReplaceNA', PACKAGE = 'metacart', x1, x2, y, vi, tau2)
}