R/RcppExports.R
In GWmodel: Geographically-Weighted Models

Documented in AICc AICc1 AICc_rss AICc_rss1 Ci_mat ehat e_vec gw_BIC gw_cv_all gw_cv_all_cuda gw_cv_all_omp gw_dist gw_fitted gw_local_r2 gwr_diag gwr_diag1 gw_reg gw_reg_1 gw_reg_2 gw_reg_all gw_reg_all_cuda gw_reg_all_omp gwr_mixed_2 gwr_mixed_trace gwr_q gw_weight gw_weight_mat gw_weight_vec new_multiscale rss scgwr_loocv scgwr_pre scgwr_reg trhat2

# This file was generated by Rcpp::compileAttributes
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
gw_dist <- function(dp.locat, rp.locat, focus, p, theta, longlat, rp.given) {
  .Call('GWmodel_gw_dist', PACKAGE = 'GWmodel', dp.locat, rp.locat, focus, p, theta, longlat, rp.given)
}
gw_weight<- function(dist, bw, kernel, adaptive){
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
  .Call('GWmodel_gw_weight', PACKAGE = 'GWmodel', dist, bw, kernel.id, adaptive)
}
gw_weight_vec<- function(vdist, bw, kernel, adaptive){
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
  .Call('GWmodel_gw_weight_vec', PACKAGE = 'GWmodel', vdist, bw, kernel.id, adaptive)
}
gw_weight_mat<- function(mdist, bw, kernel, adaptive){
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
  .Call('GWmodel_gw_weight_mat', PACKAGE = 'GWmodel', mdist, bw, kernel.id, adaptive)
}
gw_reg <- function(x, y, w, hatmatrix,focus) {
    .Call('GWmodel_gw_reg', PACKAGE = 'GWmodel', x, y, w, hatmatrix,focus)
}
gw_reg_1 <- function(x, y, w) {
    .Call('GWmodel_gw_reg_1', PACKAGE = 'GWmodel', x, y, w)
}
trhat2<- function(S)
{
    .Call('GWmodel_trhat2', PACKAGE = 'GWmodel', S)
}
gw_fitted <- function(X, beta) {
    .Call('GWmodel_fitted', PACKAGE = 'GWmodel', X, beta)
}
ehat <- function(y, X, beta) {
    .Call('GWmodel_ehat', PACKAGE = 'GWmodel', y, X, beta)
}

rss <- function(y, X, beta) {
    .Call('GWmodel_rss', PACKAGE = 'GWmodel', y, X, beta)
}

gwr_diag <- function(y,x, beta, S) {
    .Call('GWmodel_gwr_diag', PACKAGE = 'GWmodel', y, x, beta, S)
}

gwr_diag1 <- function(y,x, beta, s_hat) {
  .Call('GWmodel_gwr_diag1', PACKAGE = 'GWmodel', y, x, beta, s_hat)
}

AICc <- function(y,x, beta, S) {
    .Call('GWmodel_AICc', PACKAGE = 'GWmodel', y,x, beta, S)
}

AICc1 <- function(y,x, beta, s_hat) {
  .Call('GWmodel_AICc1', PACKAGE = 'GWmodel', y,x, beta, s_hat)
}

AICc_rss <- function(y,x, beta, S) {
    .Call('GWmodel_AICc_rss', PACKAGE = 'GWmodel', y,x, beta, S)
}

AICc_rss1 <- function(y,x, beta, s_hat) {
  .Call('GWmodel_AICc_rss1', PACKAGE = 'GWmodel', y,x, beta, s_hat)
}
Ci_mat <- function(x, w) {
    .Call('GWmodel_Ci_mat', PACKAGE = 'GWmodel', x, w)
}
gw_local_r2 <- function(dp, dybar2, dyhat2, dm_given, dmat, p, theta, longlat, bw, kernel, adaptive) {
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
  .Call('GWmodel_gw_local_r2', PACKAGE = 'GWmodel', dp, dybar2, dyhat2, dm_given, dmat, p, theta, longlat, bw, kernel.id, adaptive)
}
gw_BIC <- function(y, x,beta, s_hat)
{
    .Call('GWmodel_BIC', PACKAGE = 'GWmodel', y, x,beta, s_hat)
}
gw_reg_2<- function(x, y, w)
{
    .Call('GWmodel_gw_reg_2', PACKAGE = 'GWmodel', x, y, w)
}
gwr_q <- function(x,  y, dMat, bw, kernel, adaptive) 
{
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
   .Call('GWmodel_gwr_q', PACKAGE = 'GWmodel', x,  y, dMat, bw, kernel.id, adaptive)  
}
#scgwr_pre(mat x, vec y, int bw, int poly, double b0, mat g0, mat neighbour)
scgwr_pre <- function(x, y, bw, poly, b0, g0, neighbour) {
    .Call('GWmodel_scgwr_pre', PACKAGE = 'GWmodel', x, y, bw, poly, b0, g0, neighbour)
}

#scgwr_reg(mat x, vec y, int bw, int poly, mat G0, mat Mx0, mat My0, mat XtX, mat XtY, mat neighbour, vec parameters);
scgwr_reg <- function(x, y, bw, poly, G0, Mx0, My0, XtX, XtY, neighbour, parameters) {
    .Call('GWmodel_scgwr_reg', PACKAGE = 'GWmodel', x, y, bw, poly, G0, Mx0, My0, XtX, XtY, neighbour, parameters)
}

#scgwr_loocv(vec target, mat x, vec y, int bw, int poly, mat Mx0, mat My0, mat XtX, mat XtY)
scgwr_loocv <- function(target, x, y, bw, poly, Mx0, My0, XtX, XtY) {
    .Call('GWmodel_scgwr_loocv', PACKAGE = 'GWmodel', target, x, y, bw, poly, Mx0, My0, XtX, XtY)
}
gw_reg_all <- function(x, y, dp.locat, rp.given, rp.locat, dm.given, dmat, hatmatrix, p, theta, longlat, bw, kernel, adaptive, ngroup = 1, igroup = 1) {
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
  .Call('GWmodel_gw_reg_all', PACKAGE = 'GWmodel', 
        x, y, dp.locat, rp.given, rp.locat, dm.given, dmat, hatmatrix, p, theta, longlat, bw, kernel.id, adaptive, ngroup, igroup - 1)
}

gw_reg_all_omp <- function(x, y, dp.locat, rp.given, rp.locat, dm.given, dmat, hatmatrix, p, theta, longlat, bw, kernel, adaptive, threads = 0, ngroup = 1, igroup = 1) {
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
  .Call('GWmodel_gw_reg_all_omp', PACKAGE = 'GWmodel', 
        x, y, dp.locat, rp.given, rp.locat, dm.given, dmat, hatmatrix, p, theta, longlat, bw, kernel.id, adaptive, threads, ngroup, igroup - 1)
}

gw_reg_all_cuda <- function(x, y, dp.locat, rp.given, rp.locat, dm.given, dmat, hatmatrix, p, theta, longlat, bw, kernel, adaptive, groupl = 0, gpuID = 1) {
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
  .Call('GWmodel_gw_reg_cuda', PACKAGE = 'GWmodel', 
        x, y, dp.locat, rp.given, rp.locat, dm.given, dmat, hatmatrix, p, theta, longlat, bw, kernel.id, adaptive, groupl, gpuID - 1)
}

gw_cv_all <- function(x, y, dp.locat, dm.given, dmat, p, theta, longlat, bw, kernel, adaptive, ngroup = 1, igroup = 1) {
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
  .Call('GWmodel_gw_cv_all', PACKAGE = 'GWmodel', 
        x, y, dp.locat, dm.given, dmat, p, theta, longlat, bw, kernel.id, adaptive, ngroup, igroup - 1)
}

gw_cv_all_omp <- function(x, y, dp.locat, dm.given, dmat, p, theta, longlat, bw, kernel, adaptive, threads = 0, ngroup = 1, igroup = 1) {
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
  .Call('GWmodel_gw_cv_all_omp', PACKAGE = 'GWmodel', 
        x, y, dp.locat, dm.given, dmat, p, theta, longlat, bw, kernel.id, adaptive, threads, ngroup, igroup - 1)
}

gw_cv_all_cuda <- function(x, y, dp.locat, dm.given, dmat, p, theta, longlat, bw, kernel, adaptive, groupl = 0, gpuID = 1) {
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
  .Call('GWmodel_gw_cv_all_cuda', PACKAGE = 'GWmodel', 
        x, y, dp.locat, dm.given, dmat, p, theta, longlat, bw, kernel.id, adaptive, groupl, gpuID - 1)
}
e_vec<- function(m,n)
{
    .Call('GWmodel_e_vec', PACKAGE = 'GWmodel', m,n)
}
gwr_mixed_trace <- function(x1, x2, y, dMat, bw, kernel, adaptive) 
{
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
   .Call('GWmodel_gwr_mixed_trace', PACKAGE = 'GWmodel', x1, x2, y, dMat, bw, kernel.id, adaptive) 
}
gwr_mixed_2 <- function(x1, x2, y, dMat, dMat.rp, bw, kernel, adaptive) 
{
  kernel.id <- 0
  kernel.id <- switch (kernel,
                       gaussian = 0,
                       exponential = 1,
                       bisquare = 2,
                       tricube  = 3,
                       boxcar   = 4)
   .Call('GWmodel_gwr_mixed_2', PACKAGE = 'GWmodel', x1, x2, y, dMat, dMat.rp, bw, kernel.id, adaptive)  
}

new_multiscale <- function(x, x1, dMatsParam, dp_locat, y, bws0, var_dMat_index, adaptive, verbose, nlower, hatmatrix, max_iterations, threshold, max_threads, variable_names, kerneln, approachn, crin, bws_reOpts) {
  .Call('_GWmodel_new_multiscale', PACKAGE = 'GWmodel', x, x1, dMatsParam, dp_locat, y, bws0, var_dMat_index, adaptive, verbose, nlower, hatmatrix, max_iterations, threshold, max_threads, variable_names, kerneln, approachn, crin, bws_reOpts)
}