Gradient of negative log likelihood posterior
CGGP_internal_gneglogpost(theta, CGGP, y, ..., return_lik = FALSE, ys = NULL, Xs = NULL, HandlingSuppData = "Correct")
Log of correlation parameters
CGGP object
CGGP$design measured values
Forces you to name remaining arguments
If yes, it returns a list with lik and glik
Supplementary output data
Supplementary input data
How should supplementary data be handled? * Correct: full likelihood with grid and supplemental data * Only: only use supplemental data * Ignore: ignore supplemental data
Vector for gradient of likelihood w.r.t. x (theta)
# NOT RUN { cg <- CGGPcreate(d=3, batchsize=20) Y <- apply(cg$design, 1, function(x){x[1]+x[2]^2}) cg <- CGGPfit(cg, Y) CGGP_internal_gneglogpost(cg$thetaMAP, CGGP=cg, y=cg$y) # }
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