R/RcppExports.R

In tensorBSS: Blind Source Separation Methods for Tensor-Valued Observations

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

rnormCube <- function(varp1, varp2, varp3) {
    .Call(`_tensorBSS_rnormCube`, varp1, varp2, varp3)
}

eigenVectors <- function(varx) {
    .Call(`_tensorBSS_eigenVectors`, varx)
}

symmetricPower <- function(varx, varr) {
    .Call(`_tensorBSS_symmetricPower`, varx, varr)
}

mFOBIMatrix <- function(varx) {
    .Call(`_tensorBSS_mFOBIMatrix`, varx)
}

mFOBIMatrixNorm <- function(varx) {
    .Call(`_tensorBSS_mFOBIMatrixNorm`, varx)
}

mJADEMatrix <- function(varx, vari, varj, varcov) {
    .Call(`_tensorBSS_mJADEMatrix`, varx, vari, varj, varcov)
}

matrixCovariance <- function(varx, varnormalize) {
    .Call(`_tensorBSS_matrixCovariance`, varx, varnormalize)
}

mAutoCovMatrix <- function(varx, varlag, varnormalize) {
    .Call(`_tensorBSS_mAutoCovMatrix`, varx, varlag, varnormalize)
}

mTGFOBIMatrix <- function(varx, varlag) {
    .Call(`_tensorBSS_mTGFOBIMatrix`, varx, varlag)
}

mTGJADEMatrix <- function(varx, vari, varj, varlags) {
    .Call(`_tensorBSS_mTGJADEMatrix`, varx, vari, varj, varlags)
}

computeh <- function(varuk, varxm, varnl) {
    .Call(`_tensorBSS_computeh`, varuk, varxm, varnl)
}

computeT <- function(varuk, varxm, varnl) {
    .Call(`_tensorBSS_computeT`, varuk, varxm, varnl)
}

computed <- function(varuk, varxm, varnl) {
    .Call(`_tensorBSS_computed`, varuk, varxm, varnl)
}

computeb <- function(varuk, varxm, varnl) {
    .Call(`_tensorBSS_computeb`, varuk, varxm, varnl)
}