R/RcppExports.R

In mdfortune/simGWAS: Simulating the expected output from a GWAS with a given causal model

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

MatrixVector <- function(matrix, vector, verbose = FALSE) {
    .Call('_simGWAS_MatrixVector', PACKAGE = 'simGWAS', matrix, vector, verbose)
}

zscore <- function(N0, N1, Ufactor, powerfactor, PX1W, PX2W) {
    .Call('_simGWAS_zscore', PACKAGE = 'simGWAS', N0, N1, Ufactor, powerfactor, PX1W, PX2W)
}

psum <- function(x, y) {
    .Call('_simGWAS_psum', PACKAGE = 'simGWAS', x, y)
}

haplabs <- function(n) {
    .Call('_simGWAS_haplabs', PACKAGE = 'simGWAS', n)
}

happrobs <- function(G, P) {
    .Call('_simGWAS_happrobs', PACKAGE = 'simGWAS', G, P)
}

combinationRefs <- function(x, cols, reference, prop, shiftSize = 2L, threads = -1L, verbose = FALSE) {
    .Call('_simGWAS_combinationRefs', PACKAGE = 'simGWAS', x, cols, reference, prop, shiftSize, threads, verbose)
}

combination2 <- function(x, cols) {
    .Call('_simGWAS_combination2', PACKAGE = 'simGWAS', x, cols)
}

wsumsq <- function(xx, yy, ww) {
    .Call('_simGWAS_wsumsq', PACKAGE = 'simGWAS', xx, yy, ww)
}