# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
getRow <- function(pBigMat, row) {
.Call(`_rMVP_getRow`, pBigMat, row)
}
glm_c <- function(y, X, iXX, pBigMat, geno_ind = NULL, marker_ind = NULL, verbose = TRUE, threads = 0L) {
.Call(`_rMVP_glm_c`, y, X, iXX, pBigMat, geno_ind, marker_ind, verbose, threads)
}
mlm_c <- function(y, X, U, vgs, pBigMat, geno_ind = NULL, marker_ind = NULL, verbose = TRUE, threads = 0L) {
.Call(`_rMVP_mlm_c`, y, X, U, vgs, pBigMat, geno_ind, marker_ind, verbose, threads)
}
vcf_parser_map <- function(vcf_file, out) {
.Call(`_rMVP_vcf_parser_map`, vcf_file, out)
}
vcf_parser_genotype <- function(vcf_file, pBigMat, maxLine, threads = 0L, verbose = TRUE) {
invisible(.Call(`_rMVP_vcf_parser_genotype`, vcf_file, pBigMat, maxLine, threads, verbose))
}
hapmap_parser_map <- function(hmp_file, out) {
.Call(`_rMVP_hapmap_parser_map`, hmp_file, out)
}
hapmap_parser_genotype <- function(hmp_file, Major, pBigMat, maxLine, threads = 0L, verbose = TRUE) {
invisible(.Call(`_rMVP_hapmap_parser_genotype`, hmp_file, Major, pBigMat, maxLine, threads, verbose))
}
numeric_scan <- function(num_file) {
.Call(`_rMVP_numeric_scan`, num_file)
}
write_bfile <- function(pBigMat, bed_file, threads = 0L, verbose = TRUE) {
invisible(.Call(`_rMVP_write_bfile`, pBigMat, bed_file, threads, verbose))
}
read_bfile <- function(bed_file, pBigMat, maxLine, threads = 0L, verbose = TRUE) {
invisible(.Call(`_rMVP_read_bfile`, bed_file, pBigMat, maxLine, threads, verbose))
}
fit_diago_brent <- function(Y, X, p_, Sigma, U, min_h2, max_h2, tol, verbose) {
.Call(`_rMVP_fit_diago_brent`, Y, X, p_, Sigma, U, min_h2, max_h2, tol, verbose)
}
crossprodcpp <- function(X) {
.Call(`_rMVP_crossprodcpp`, X)
}
geninv <- function(GG) {
.Call(`_rMVP_geninv`, GG)
}
impute_marker <- function(pBigMat, threads = 0L, verbose = TRUE) {
invisible(.Call(`_rMVP_impute_marker`, pBigMat, threads, verbose))
}
hasNA <- function(pBigMat, geno_ind = NULL, threads = 1L) {
.Call(`_rMVP_hasNA`, pBigMat, geno_ind, threads)
}
BigRowMean <- function(pBigMat, threads = 0L, geno_ind = NULL) {
.Call(`_rMVP_BigRowMean`, pBigMat, threads, geno_ind)
}
kin_cal_m <- function(pBigMat, threads = 0L, verbose = TRUE) {
.Call(`_rMVP_kin_cal_m`, pBigMat, threads, verbose)
}
kin_cal_s <- function(pBigMat, threads = 0L, mkl = FALSE, verbose = TRUE) {
.Call(`_rMVP_kin_cal_s`, pBigMat, threads, mkl, verbose)
}
kin_cal <- function(pBigMat, geno_ind = NULL, marker_ind = NULL, threads = 0L, step = 10000L, mkl = FALSE, verbose = TRUE) {
.Call(`_rMVP_kin_cal`, pBigMat, geno_ind, marker_ind, threads, step, mkl, verbose)
}
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