R/mgcv.R

In npiv: Nonparametric Instrumental Variables Estimation and Inference

## Copyright (C) 2000-2012 Simon N. Wood  simon.wood@r-project.org
## 
## This program is free software; you can redistribute it and/or
## modify it under the terms of the GNU General Public License
## as published by the Free Software Foundation; either version 2
## of the License, or (at your option) any later version.
## 
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
## GNU General Public License for more details.
## (www.gnu.org/copyleft/gpl.html)
## 
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## along with this program; if not, write to the Free Software
## Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307,
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tensor.prod.model.matrix <- function(X) {
# X is a list of model matrices, from which a tensor product model matrix is to be produced.
# e.g. ith row is basically X[[1]][i,]%x%X[[2]][i,]%x%X[[3]][i,], but this routine works 
# column-wise, for efficiency, and does work in compiled code.
  m <- length(X)              ## number to row tensor product
  d <- unlist(lapply(X,ncol)) ## dimensions of each X
  n <- nrow(X[[1]])           ## columns in each X
  X <- as.numeric(unlist(X))  ## append X[[i]]s columnwise
  T <- numeric(n*prod(d))     ## storage for result
  .Call(mgcv_tmm,X,T,d,m,n)   ## produce product
  ## Give T attributes of matrix. Note that initializing T as a matrix 
  ## requires more time than forming the row tensor product itself (R 3.0.1)
  attr(T,"dim") <- c(n,prod(d)) 
  class(T) <- "matrix"
  T
} ## end tensor.prod.model.matrix