R/RcppExports.R

In HarrisQ/linearsdr: Linear Sufficient Reduction Methods

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

#' @noRd
#' @export
center_cpp <- function(x, center = NULL) {
    .Call(`_linearsdr_center_cpp`, x, center)
}

#' @noRd
#' @export
stand_vec_cpp <- function(x) {
    .Call(`_linearsdr_stand_vec_cpp`, x)
}

#' @noRd
#' @export
normalize_cpp <- function(x) {
    .Call(`_linearsdr_normalize_cpp`, x)
}

#' @noRd
#' @export
euc_norm_cpp <- function(x) {
    .Call(`_linearsdr_euc_norm_cpp`, x)
}

#' @noRd
#' @export
list_sum <- function(listA, listB) {
    .Call(`_linearsdr_list_sum`, listA, listB)
}

#' General Matrix Power Function
#' 
#' This is an internal function used for computing matrix powers
#' 
#' @param a a square matrix 
#' @param alpha power of matrix to be taken 
#' @param lead number of leading eigenvalues to consider; default is all
#' @param ignore decimal place to ignore; default is 10^(-15)
#'
#' @return a matrix to the power alpha
#'
#' @keywords internal
#' 
#' @noRd
#' @export
matpower_cpp <- function(a, alpha, lead = NULL, ignore = NULL) {
    .Call(`_linearsdr_matpower_cpp`, a, alpha, lead, ignore)
}

#' @noRd
#' @export
matcenter_cpp <- function(x_matrix, index = NULL, x0 = NULL) {
    .Call(`_linearsdr_matcenter_cpp`, x_matrix, index, x0)
}

#' @noRd
#' @export
eigen_cpp <- function(A) {
    .Call(`_linearsdr_eigen_cpp`, A)
}

#' @noRd
#' @export
gev_cpp <- function(A, B) {
    .Call(`_linearsdr_gev_cpp`, A, B)
}

#' @noRd
#' @export
inv_sympd_cpp <- function(A) {
    .Call(`_linearsdr_inv_sympd_cpp`, A)
}

#' @noRd
#' @export
sqrtmat_cpp <- function(A) {
    .Call(`_linearsdr_sqrtmat_cpp`, A)
}

#' @noRd
#' @export
chol_cpp <- function(A) {
    .Call(`_linearsdr_chol_cpp`, A)
}

#' @noRd
#' @export
solve_cpp <- function(A, B) {
    .Call(`_linearsdr_solve_cpp`, A, B)
}

#' @noRd
#' @export
gauss_kern_cpp <- function(centered_data, bw) {
    .Call(`_linearsdr_gauss_kern_cpp`, centered_data, bw)
}

#' @noRd
#' @export
wls_cpp <- function(x_matrix, y_matrix, weights, reg) {
    .Call(`_linearsdr_wls_cpp`, x_matrix, y_matrix, weights, reg)
}

mgauss_loss_j_made <- function(c, xj, y_matrix, wj, ahat, Dhat) {
    .Call(`_linearsdr_mgauss_loss_j_made`, c, xj, y_matrix, wj, ahat, Dhat)
}

mgauss_loss_made <- function(c, x_matrix, y_matrix, bw, ahat_list, Dhat_list, r_mat) {
    .Call(`_linearsdr_mgauss_loss_made`, c, x_matrix, y_matrix, bw, ahat_list, Dhat_list, r_mat)
}

mgauss_score_j_made <- function(c, xj, y_matrix, wj, ahat, Dhat) {
    .Call(`_linearsdr_mgauss_score_j_made`, c, xj, y_matrix, wj, ahat, Dhat)
}

mgauss_score_made <- function(c, x_matrix, y_matrix, bw, ahat_list, Dhat_list, r_mat) {
    .Call(`_linearsdr_mgauss_score_made`, c, x_matrix, y_matrix, bw, ahat_list, Dhat_list, r_mat)
}

mgauss_info_j_made <- function(c, xj, y_matrix, wj, ahat, Dhat) {
    .Call(`_linearsdr_mgauss_info_j_made`, c, xj, y_matrix, wj, ahat, Dhat)
}

mgauss_info_made <- function(c, x_matrix, y_matrix, bw, ahat_list, Dhat_list, r_mat) {
    .Call(`_linearsdr_mgauss_info_made`, c, x_matrix, y_matrix, bw, ahat_list, Dhat_list, r_mat)
}

mnY_to_mvY <- function(mn_y, m_classes, ytype) {
    .Call(`_linearsdr_mnY_to_mvY`, mn_y, m_classes, ytype)
}

emp_logit <- function(y_matrix, k_vec, tune) {
    .Call(`_linearsdr_emp_logit`, y_matrix, k_vec, tune)
}

emp_adcat <- function(y_matrix, tune) {
    .Call(`_linearsdr_emp_adcat`, y_matrix, tune)
}

dot_b_multinom <- function(lin_can_par, k_i, link) {
    .Call(`_linearsdr_dot_b_multinom`, lin_can_par, k_i, link)
}

mn_loss_j <- function(c, vj, y_datta, wj, lambda, link, k) {
    .Call(`_linearsdr_mn_loss_j`, c, vj, y_datta, wj, lambda, link, k)
}

mn_score_j <- function(c, vj, y_datta, wj, lambda, link, k) {
    .Call(`_linearsdr_mn_score_j`, c, vj, y_datta, wj, lambda, link, k)
}

mn_info_j <- function(c, vj, y_datta, wj, lambda, link, k) {
    .Call(`_linearsdr_mn_info_j`, c, vj, y_datta, wj, lambda, link, k)
}

mn_loss_j_made <- function(c, xj, y_matrix, wj, ahat, Dhat, link, k) {
    .Call(`_linearsdr_mn_loss_j_made`, c, xj, y_matrix, wj, ahat, Dhat, link, k)
}

mn_loss_made <- function(c, x_matrix, y_matrix, bw, ahat_list, Dhat_list, link, k, r_mat) {
    .Call(`_linearsdr_mn_loss_made`, c, x_matrix, y_matrix, bw, ahat_list, Dhat_list, link, k, r_mat)
}

mn_score_j_made <- function(c, xj, y_matrix, wj, ahat, Dhat, link, k) {
    .Call(`_linearsdr_mn_score_j_made`, c, xj, y_matrix, wj, ahat, Dhat, link, k)
}

mn_score_made <- function(c, x_matrix, y_matrix, bw, ahat_list, Dhat_list, link, k, r_mat) {
    .Call(`_linearsdr_mn_score_made`, c, x_matrix, y_matrix, bw, ahat_list, Dhat_list, link, k, r_mat)
}

mn_info_j_made <- function(c, xj, y_matrix, wj, ahat, Dhat, link, k) {
    .Call(`_linearsdr_mn_info_j_made`, c, xj, y_matrix, wj, ahat, Dhat, link, k)
}

list_mean <- function(est_list) {
    .Call(`_linearsdr_list_mean`, est_list)
}

aD_j_newton <- function(init, vj, y_datta, wj, lambda, link, k, tol, max_iter, test) {
    .Call(`_linearsdr_aD_j_newton`, init, vj, y_datta, wj, lambda, link, k, tol, max_iter, test)
}

vecB_hat <- function(c0, score_list, info_list) {
    .Call(`_linearsdr_vecB_hat`, c0, score_list, info_list)
}

aD_j_cg <- function(init, vj, y_datta, wj, lambda, link, k, control_list, test) {
    .Call(`_linearsdr_aD_j_cg`, init, vj, y_datta, wj, lambda, link, k, control_list, test)
}

vecB_cg <- function(init, x_datta, y_datta, bw, ahat_list, Dhat_list, link, k, r_mat, control_list, test) {
    .Call(`_linearsdr_vecB_cg`, init, x_datta, y_datta, bw, ahat_list, Dhat_list, link, k, r_mat, control_list, test)
}

rcpparma_hello_world <- function() {
    .Call(`_linearsdr_rcpparma_hello_world`)
}

rcpparma_outerproduct <- function(x) {
    .Call(`_linearsdr_rcpparma_outerproduct`, x)
}

rcpparma_innerproduct <- function(x) {
    .Call(`_linearsdr_rcpparma_innerproduct`, x)
}

rcpparma_bothproducts <- function(x) {
    .Call(`_linearsdr_rcpparma_bothproducts`, x)
}