# 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.ynew" <- function(out, y = NULL, yM = NULL) {
    #
    # calculates the collapsed y (weighted) mean vector based on the
    # X matrix and weights from the out object.
    # or just passes through the collapsed mean data if passed.
    #
    #
    # If there are no replicated obs. then return the full vector
    # pure error ss is zero
    #
    shat.rep <- NA
    shat.pure.error <- NA
    pure.ss <- 0
    # if no y's are given then it is assumed that one should use the
    # yM from the original data used to create the Krig object
    if (is.null(yM) & is.null(y)) {
        yM <- out$yM
    }
    #
    # case when yM is passed no calculations are needed
    #
    if (!is.null(yM)) {
        return(list(yM = as.matrix(yM), shat.rep = NA, shat.pure.error = NA, 
            pure.ss = 0))
    }
    #
    # no reps case
    #
    if (length(unique(out$rep.info)) == out$N) {
        return(list(yM = as.matrix(y), shat.rep = NA, shat.pure.error = NA, 
            pure.ss = 0))
    }
    #
    #  check that y is the right length
    #
    if (length(y) != out$N) {
        stop(" the new y vector is the wrong length!")
    }
    #
    # case when full y data is passed and replicate means need to be found
    #
    if (length(unique(out$rep.info)) < out$N) {
        #
        # calculate means by pooling Replicated obseravations but use the
        # the right weighting.
        #
        rep.info.aov <- fast.1way(out$rep.info, y, out$weights)[c("means", 
            "MSE", "SSE")]
        shat.pure.error <- sqrt(rep.info.aov$MSE)
        shat.rep <- shat.pure.error
        return(list(yM = rep.info.aov$means, shat.rep = shat.rep, 
            shat.pure.error = shat.pure.error, pure.ss = rep.info.aov$SSE))
    }
}