R/RcppExports.R

In Ali-Mahzarnia/222: Computes the solution path of the multivariate Scalar-on-Functional Elastic Net regression in serial and parallel

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

solvecpp <- function(A) {
    .Call(`_MFSGrp_solvecpp`, A)
}

maxeigencpp <- function(X) {
    .Call(`_MFSGrp_maxeigencpp`, X)
}

normcpp <- function(x, A, euc = TRUE) {
    .Call(`_MFSGrp_normcpp`, x, A, euc)
}

softcpp <- function(x, A, lambda, euc = TRUE) {
    .Call(`_MFSGrp_softcpp`, x, A, lambda, euc)
}

softscadcpp <- function(x, Gram, lambda, rho, a = 3.7, euc = TRUE) {
    .Call(`_MFSGrp_softscadcpp`, x, Gram, lambda, rho, a, euc)
}

foldcpp <- function(Y, X, basisno, tt, lambda, alpha, GG, lambdader, part, rho, Penalty, GGder, K, Gram, oldGram, n, p, m, kf = 10L, euc = TRUE, Path = FALSE, eps = 1e-08, maxit = 1000L, a = 3.7, id = 1L, idmax = 1L, alphanet = FALSE) {
    .Call(`_MFSGrp_foldcpp`, Y, X, basisno, tt, lambda, alpha, GG, lambdader, part, rho, Penalty, GGder, K, Gram, oldGram, n, p, m, kf, euc, Path, eps, maxit, a, id, idmax, alphanet)
}