Nothing
gpOut <-
function(model, x) {
if (nargs() < 2) {
## This implies evaluate for the training data.
mu = model$mu ## bug: values of mu, varsigma not used
varsigma = model$varSigma
} else {
if ('noise' %in% names(model)) {
# [mu, varsigma] = gpPosteriorMeanVar(model, x)
meanVar = gpPosteriorMeanVar(model, x, varsigma.return=TRUE)
y = noiseOut(model$noise, meanVar$mu, meanVar$varsigma)
} else
y = gpPosteriorMeanVar(model, x)
}
return(y)
}
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