Nothing
rbfKernGradient <-
function (kern, x, x2, covGrad) {
if ( nargs()==3 ) {
k <- rbfKernCompute(kern, x)
dist2xx <- .dist2(x, x)
covGrad <- x2
} else if ( nargs()==4 ) {
k <- rbfKernCompute(kern, x, x2)
dist2xx <- .dist2(x, x2)
}
g <- array()
if ("isNormalised" %in% names(kern) && kern$isNormalised) {
g[1] <- -0.5*sum(covGrad*k*dist2xx) +
0.5 * sum(covGrad*k)/kern$inverseWidth
}
else {
g[1] <- -0.5*sum(covGrad*k*dist2xx)
}
g[2] <- sum(covGrad*k)/kern$variance
if ( any(is.nan(g)) )
warning("g is NaN.")
return (g)
}
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