R/RcppExports.R

In missSBM: Handling Missing Data in Stochastic Block Models

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

vLL_complete_sparse_bernoulli_nocovariate <- function(Y, R, Z, theta, pi) {
    .Call(`_missSBM_vLL_complete_sparse_bernoulli_nocovariate`, Y, R, Z, theta, pi)
}

vLL_complete_sparse_bernoulli_covariates <- function(Y, R, M, Z, Gamma, pi) {
    .Call(`_missSBM_vLL_complete_sparse_bernoulli_covariates`, Y, R, M, Z, Gamma, pi)
}

M_step_sparse_bernoulli_nocovariate <- function(Y, R, Z, sym = TRUE) {
    .Call(`_missSBM_M_step_sparse_bernoulli_nocovariate`, Y, R, Z, sym)
}

M_step_sparse_bernoulli_covariates <- function(init_param, Y, R, X, Z, sym, configuration) {
    .Call(`_missSBM_M_step_sparse_bernoulli_covariates`, init_param, Y, R, X, Z, sym, configuration)
}

E_step_sparse_bernoulli_nocovariate <- function(Y, R, Z, theta, pi, rescale = TRUE) {
    .Call(`_missSBM_E_step_sparse_bernoulli_nocovariate`, Y, R, Z, theta, pi, rescale)
}

E_step_sparse_bernoulli_covariates <- function(Y, R, M, Z, Gamma, pi, symmetric = TRUE, rescale = TRUE) {
    .Call(`_missSBM_E_step_sparse_bernoulli_covariates`, Y, R, M, Z, Gamma, pi, symmetric, rescale)
}

kmeans_cpp <- function(coordinates, input_centroids) {
    .Call(`_missSBM_kmeans_cpp`, coordinates, input_centroids)
}

cpp_test_nlopt <- function() {
    .Call(`_missSBM_cpp_test_nlopt`)
}

cpp_test_packing <- function() {
    .Call(`_missSBM_cpp_test_packing`)
}

roundProduct <- function(covariates_list, beta) {
    .Call(`_missSBM_roundProduct`, covariates_list, beta)
}