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Tip revision: 8eab500c3dad2103092ff68706417414fe53e16b authored by Doug Nychka on 22 September 2009, 20:23:49 UTC
version 6.01
Tip revision: 8eab500
Krig.Amatrix.R
# fields, Tools for spatial data
# Copyright 2004-2007, Institute for Mathematics Applied Geosciences
# University Corporation for Atmospheric Research
# Licensed under the GPL -- www.gpl.org/licenses/gpl.html
Krig.Amatrix <- function(object, x0 = object$x, lambda = NULL, 
    eval.correlation.model = FALSE, ...) {
    if (is.null(lambda)) {
        lambda <- object$lambda
    }
    M <- nrow(object$xM)
    N <- nrow(x0)
    # create output matrix
    out <- matrix(NA, N, M)
    #
    # loop through unique data locations predicting response
    # using unit vector
    # NOTE that the y vector has already been collapsed onto means.
    #
    for (k in 1:M) {
        ytemp <- rep(0, M)
        ytemp[k] <- 1
        out[, k] <- predict(object, x = x0, yM = ytemp, lambda = lambda, 
            eval.correlation.model = eval.correlation.model, 
            ...)
    }
    return(out)
}
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