Revision 6a574ee78277f7f38ae7939a12894c1616dc61eb authored by Douglas Nychka on 16 October 2015, 01:28:36 UTC, committed by cran-robot on 16 October 2015, 01:28:36 UTC
1 parent fd0fd2f
Krig.test.W.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
library(fields)
options( echo=FALSE)
test.for.zero.flag<- 1
#
#
# test of off diagonal weight matrix for obs
# Check against linear algebra
#
#cat("A very nasty case with off diagonal weights",fill=TRUE)
set.seed(123)
x<- matrix( runif( 30), 15,2)
y<- rnorm( 15)*.01 + x[,1]**2 + x[,2]**2
#weights<- rep( 1, 15)
weights<- runif(15)*10
# WBW
# double check that just diagonals work.
lambda.test<- .6
Krig( x,y,cov.function=Exp.cov,weights=weights)-> out
Krig( x,y,cov.function=Exp.cov,weights=weights, lambda=lambda.test)-> out2
Krig.coef( out, lambda=lambda.test)-> test
W<- diag( weights)
W2<- diag( sqrt(weights))
K<- Exp.cov(x,x)
M<- (lambda.test*solve(W) + K);T<- fields.mkpoly(x, 2)
temp.d<- c(solve( t(T) %*% solve( M)%*%T) %*% t(T)%*% solve( M) %*%y)
temp.c<- solve( M)%*% (y - T%*% temp.d)
#
# test for d coefficients
test.for.zero( test$d, out2$d, tag=" d coef diag W fixed lam")
test.for.zero( temp.d, out2$d, tag=" d coef diag W")
# test for c coefficents
test.for.zero( test$c, out2$c, tag="c coef diag W fixed lam" )
test.for.zero( temp.c, out2$c, tag="c coef diag W " )
# the full monty
temp.wght<- function(x, alpha=.1){
Exp.cov( x, theta=alpha) }
Krig( x,y,
cov.function=Exp.cov,weights=weights, wght.function= temp.wght,
)-> out.new
W2<-out.new$W2
W<- out.new$W
test.for.zero( c( W2%*%W2), c( W), tag=" sqrt of W")
Krig( x,y, cov.function=Exp.cov,weights=weights, W= out.new$W)-> temp
test.for.zero( predict(temp, y= y), predict(out.new,y=y),
tag=" Test of passing W explicitly")
K<- Exp.cov(x,x); lambda.test<- .6;
M<- (lambda.test*solve(W) + K);T<- fields.mkpoly(x, 2)
temp.d<- c(solve( t(T) %*% solve( M)%*%T) %*% t(T)%*% solve( M) %*%y)
temp.c<- solve( M)%*% (y - T%*% temp.d)
#
Krig.coef( out.new,lambda=lambda.test )-> out2
test.for.zero( temp.d, out2$d, tag=" d coef full W")
# test for c coefficents
test.for.zero( temp.c, out2$c, tag="c coef full W" )
####
### testing the GCV function
lambda<- out.new$lambda
Krig.Amatrix( out.new, lambda=lambda)-> Alam
test.for.zero( Alam%*%y , predict(out.new), tag="A matrix")
N<- length( y)
test<- sum( diag( Alam))
# compare to
test2<- out.new$eff.df
test.for.zero( test,test2, tag=" check trace of A")
Krig.fgcv.one( lam=lambda, out.new)-> test
# compare to
test2<- (1/N)*sum(
(out.new$W2%*%(y - c(Alam%*% y) ))**2
) / (1- sum(diag( Alam))/N)**2
test.for.zero( test,test2,tol=.5e-7, tag="GCV one" )
cat( "all done testing off diag W case", fill=TRUE)
options( echo=TRUE)
![swh spinner](/static/img/swh-spinner.gif)
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