https://github.com/cran/fields
Tip revision: 32c60b2ec8167f7d2b26f55147b4e380a8ad77b3 authored by Doug Nychka on 25 September 2011, 00:00:00 UTC
version 6.6.1
version 6.6.1
Tip revision: 32c60b2
rad.cov.r
# fields, Tools for spatial data
# Copyright 2004-2011, Institute for Mathematics Applied Geosciences
# University Corporation for Atmospheric Research
# Licensed under the GPL -- www.gpl.org/licenses/gpl.html
"Rad.cov" <- function(x1, x2, p = 1, m=NA,with.log = TRUE,
with.constant = TRUE, C = NA, marginal = FALSE, derivative = 0) {
#
# mth order thin plate spline radial basis functions
# in d dimensions
# usually called with p 2m-d
# marginal dummy argument
# this should only be called within predict.se.Krig
# and provides the correct calculation. Because this is
# a generalized covariance the marginal variance is not really
# defined.
#
if (marginal) {
return(rep(0, nrow(x1)))
}
#
# coerce locations to matrices, if x2 is missing use x1
if (!is.matrix(x1))
x1 <- as.matrix(x1)
if (!is.matrix(x2))
x2 <- as.matrix(x2)
d <- ncol(x1)
n1 <- nrow(x1)
n2 <- nrow(x2)
if( is.na(m)){
m <- (d + p)/2}
else{
p <- 2*m -d}
if( p < 0 ) {
stop(" p is negative (m possibly too small)")}
# parameter list to send to the FORTRAN
par <- c(p/2, ifelse((d%%2 == 0) & (with.log), 1, 0))
#
# multiply by constant if requested
rbf.constant <- ifelse(with.constant, radbas.constant(m,
d), 1)
# compute matrix in FORTRAN
if (is.na(C[1])) {
temp <- .Fortran("radbas", nd = as.integer(d), x1 = as.double(x1),
n1 = as.integer(n1), x2 = as.double(x2), n2 = as.integer(n2),
par = as.double(par), k = as.double(rep(0, n1 * n2)))
return(rbf.constant * matrix(temp$k, ncol = n2, nrow = n1))
}
else {
# do cross covariance matrix multiplication in FORTRAN
if (derivative == 0) {
# evaluate function not partial derivatives.
C <- as.matrix(C)
n3 <- ncol(C)
temp <- .Fortran("multrb", nd = as.integer(d), x1 = as.double(x1),
n1 = as.integer(n1), x2 = as.double(x2), n2 = as.integer(n2),
par = as.double(par), c = as.double(C), n3 = as.integer(n3),
h = as.double(rep(0, n1 * n3)), work = as.double(rep(0,
n2)))$h
return(rbf.constant * matrix(temp, nrow = n1, ncol = n3))
}
else {
if (ncol(C) > 1) {
stop("Can only evaluate derivatives on one spline fit")
}
temp <- .Fortran("mltdrb", nd = as.integer(d), x1 = as.double(x1),
n1 = as.integer(n1), x2 = as.double(x2), n2 = as.integer(n2),
par = as.double(par), c = as.double(C), h = as.double(rep(0,
n1 * d)), work = as.double(rep(0, n2)))$h
return(rbf.constant * matrix(temp, nrow = n1, ncol = d))
}
}
stop("should not get here!")
}