R/RcppExports.R

In spEDM: Spatial Empirical Dynamic Modeling

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

RcppSimplexForecast <- function(embedding, target, lib, pred, num_neighbors) {
    .Call(`_spEDM_RcppSimplexForecast`, embedding, target, lib, pred, num_neighbors)
}

RcppSMapForecast <- function(embedding, target, lib, pred, num_neighbors, theta) {
    .Call(`_spEDM_RcppSMapForecast`, embedding, target, lib, pred, num_neighbors, theta)
}

RcppIntersectionCardinality <- function(embedding_x, embedding_y, lib, pred, num_neighbors, n_excluded, threads, progressbar) {
    .Call(`_spEDM_RcppIntersectionCardinality`, embedding_x, embedding_y, lib, pred, num_neighbors, n_excluded, threads, progressbar)
}

RcppLocateGridIndices <- function(curRow, curCol, totalRow, totalCol) {
    .Call(`_spEDM_RcppLocateGridIndices`, curRow, curCol, totalRow, totalCol)
}

RcppRowColFromGrid <- function(cellNum, totalCol) {
    .Call(`_spEDM_RcppRowColFromGrid`, cellNum, totalCol)
}

RcppLaggedVar4Grid <- function(mat, lagNum) {
    .Call(`_spEDM_RcppLaggedVar4Grid`, mat, lagNum)
}

RcppGenGridEmbeddings <- function(mat, E, tau) {
    .Call(`_spEDM_RcppGenGridEmbeddings`, mat, E, tau)
}

RcppSimplex4Grid <- function(mat, lib, pred, E, b, tau, threads) {
    .Call(`_spEDM_RcppSimplex4Grid`, mat, lib, pred, E, b, tau, threads)
}

RcppSMap4Grid <- function(mat, lib, pred, theta, E, tau, b, threads) {
    .Call(`_spEDM_RcppSMap4Grid`, mat, lib, pred, theta, E, tau, b, threads)
}

RcppMultiView4Grid <- function(xMatrix, yMatrix, lib, pred, E, tau, b, top, nvar, threads) {
    .Call(`_spEDM_RcppMultiView4Grid`, xMatrix, yMatrix, lib, pred, E, tau, b, top, nvar, threads)
}

RcppGCCM4Grid <- function(xMatrix, yMatrix, libsizes, lib, pred, E, tau, b, simplex, theta, threads, parallel_level, progressbar) {
    .Call(`_spEDM_RcppGCCM4Grid`, xMatrix, yMatrix, libsizes, lib, pred, E, tau, b, simplex, theta, threads, parallel_level, progressbar)
}

RcppSCPCM4Grid <- function(xMatrix, yMatrix, zMatrix, libsizes, lib, pred, E, tau, b, simplex, theta, threads, parallel_level, cumulate, progressbar) {
    .Call(`_spEDM_RcppSCPCM4Grid`, xMatrix, yMatrix, zMatrix, libsizes, lib, pred, E, tau, b, simplex, theta, threads, parallel_level, cumulate, progressbar)
}

RcppGCMC4Grid <- function(xMatrix, yMatrix, lib, pred, E, tau, b, max_r, threads, progressbar) {
    .Call(`_spEDM_RcppGCMC4Grid`, xMatrix, yMatrix, lib, pred, E, tau, b, max_r, threads, progressbar)
}

DetectMaxNumThreads <- function() {
    .Call(`_spEDM_DetectMaxNumThreads`)
}

OptEmbedDim <- function(Emat) {
    .Call(`_spEDM_OptEmbedDim`, Emat)
}

OptThetaParm <- function(Thetamat) {
    .Call(`_spEDM_OptThetaParm`, Thetamat)
}

MatNotNAIndice <- function(mat, byrow = TRUE) {
    .Call(`_spEDM_MatNotNAIndice`, mat, byrow)
}

RcppLaggedNeighbor4Lattice <- function(nb, lagNum) {
    .Call(`_spEDM_RcppLaggedNeighbor4Lattice`, nb, lagNum)
}

RcppLaggedVar4Lattice <- function(vec, nb, lagNum) {
    .Call(`_spEDM_RcppLaggedVar4Lattice`, vec, nb, lagNum)
}

RcppGenLatticeEmbeddings <- function(vec, nb, E, tau) {
    .Call(`_spEDM_RcppGenLatticeEmbeddings`, vec, nb, E, tau)
}

RcppSimplex4Lattice <- function(x, nb, lib, pred, E, b, tau, threads) {
    .Call(`_spEDM_RcppSimplex4Lattice`, x, nb, lib, pred, E, b, tau, threads)
}

RcppSMap4Lattice <- function(x, nb, lib, pred, theta, E, tau, b, threads) {
    .Call(`_spEDM_RcppSMap4Lattice`, x, nb, lib, pred, theta, E, tau, b, threads)
}

RcppMultiView4Lattice <- function(x, y, nb, lib, pred, E, tau, b, top, nvar, threads) {
    .Call(`_spEDM_RcppMultiView4Lattice`, x, y, nb, lib, pred, E, tau, b, top, nvar, threads)
}

RcppGCCM4Lattice <- function(x, y, nb, libsizes, lib, pred, E, tau, b, simplex, theta, threads, parallel_level, progressbar) {
    .Call(`_spEDM_RcppGCCM4Lattice`, x, y, nb, libsizes, lib, pred, E, tau, b, simplex, theta, threads, parallel_level, progressbar)
}

RcppSCPCM4Lattice <- function(x, y, z, nb, libsizes, lib, pred, E, tau, b, simplex, theta, threads, parallel_level, cumulate, progressbar) {
    .Call(`_spEDM_RcppSCPCM4Lattice`, x, y, z, nb, libsizes, lib, pred, E, tau, b, simplex, theta, threads, parallel_level, cumulate, progressbar)
}

RcppGCMC4Lattice <- function(x, y, nb, lib, pred, E, tau, b, max_r, threads, progressbar) {
    .Call(`_spEDM_RcppGCMC4Lattice`, x, y, nb, lib, pred, E, tau, b, max_r, threads, progressbar)
}

RcppFactorial <- function(n) {
    .Call(`_spEDM_RcppFactorial`, n)
}

RcppCombine <- function(n, k) {
    .Call(`_spEDM_RcppCombine`, n, k)
}

RcppMean <- function(vec, NA_rm = FALSE) {
    .Call(`_spEDM_RcppMean`, vec, NA_rm)
}

RcppSum <- function(vec, NA_rm = FALSE) {
    .Call(`_spEDM_RcppSum`, vec, NA_rm)
}

RcppVariance <- function(vec, NA_rm = FALSE) {
    .Call(`_spEDM_RcppVariance`, vec, NA_rm)
}

RcppCovariance <- function(vec1, vec2, NA_rm = FALSE) {
    .Call(`_spEDM_RcppCovariance`, vec1, vec2, NA_rm)
}

RcppMAE <- function(vec1, vec2, NA_rm = FALSE) {
    .Call(`_spEDM_RcppMAE`, vec1, vec2, NA_rm)
}

RcppRMSE <- function(vec1, vec2, NA_rm = FALSE) {
    .Call(`_spEDM_RcppRMSE`, vec1, vec2, NA_rm)
}

RcppCumSum <- function(vec) {
    .Call(`_spEDM_RcppCumSum`, vec)
}

RcppAbsDiff <- function(vec1, vec2) {
    .Call(`_spEDM_RcppAbsDiff`, vec1, vec2)
}

RcppSumNormalize <- function(vec, NA_rm = FALSE) {
    .Call(`_spEDM_RcppSumNormalize`, vec, NA_rm)
}

RcppArithmeticSeq <- function(from, to, length_out) {
    .Call(`_spEDM_RcppArithmeticSeq`, from, to, length_out)
}

RcppDistance <- function(vec1, vec2, L1norm = FALSE, NA_rm = FALSE) {
    .Call(`_spEDM_RcppDistance`, vec1, vec2, L1norm, NA_rm)
}

RcppPearsonCor <- function(y, y_hat, NA_rm = FALSE) {
    .Call(`_spEDM_RcppPearsonCor`, y, y_hat, NA_rm)
}

RcppPartialCor <- function(y, y_hat, controls, NA_rm = FALSE, linear = FALSE) {
    .Call(`_spEDM_RcppPartialCor`, y, y_hat, controls, NA_rm, linear)
}

RcppPartialCorTrivar <- function(y, y_hat, control, NA_rm = FALSE, linear = FALSE) {
    .Call(`_spEDM_RcppPartialCorTrivar`, y, y_hat, control, NA_rm, linear)
}

RcppCorSignificance <- function(r, n, k = 0L) {
    .Call(`_spEDM_RcppCorSignificance`, r, n, k)
}

RcppCorConfidence <- function(r, n, k = 0L, level = 0.05) {
    .Call(`_spEDM_RcppCorConfidence`, r, n, k, level)
}

RcppDeLongAUCConfidence <- function(cases, controls, direction, level = 0.05) {
    .Call(`_spEDM_RcppDeLongAUCConfidence`, cases, controls, direction, level)
}

RcppCMCTest <- function(cases, direction, level = 0.05, num_samples = 0L) {
    .Call(`_spEDM_RcppCMCTest`, cases, direction, level, num_samples)
}

RcppMatDistance <- function(mat, L1norm = FALSE, NA_rm = FALSE) {
    .Call(`_spEDM_RcppMatDistance`, mat, L1norm, NA_rm)
}

RcppKNNIndice <- function(embedding_space, target_idx, k) {
    .Call(`_spEDM_RcppKNNIndice`, embedding_space, target_idx, k)
}

RcppDistKNNIndice <- function(dist_mat, target_idx, k) {
    .Call(`_spEDM_RcppDistKNNIndice`, dist_mat, target_idx, k)
}

RcppLinearTrendRM <- function(vec, xcoord, ycoord, NA_rm = FALSE) {
    .Call(`_spEDM_RcppLinearTrendRM`, vec, xcoord, ycoord, NA_rm)
}

RcppSVD <- function(X) {
    .Call(`_spEDM_RcppSVD`, X)
}

RcppDeLongPlacements <- function(cases, controls, direction) {
    .Call(`_spEDM_RcppDeLongPlacements`, cases, controls, direction)
}