CGGP_internal_gneglogpost: Gradient of negative log likelihood posterior

In CGGP: Composite Grid Gaussian Processes

Description

Gradient of negative log likelihood posterior

Usage

CGGP_internal_gneglogpost(
  theta,
  CGGP,
  y,
  ...,
  return_lik = FALSE,
  ys = NULL,
  Xs = NULL,
  HandlingSuppData = "Correct"
)

Arguments

theta	Log of correlation parameters
CGGP	CGGP object
y	CGGP$design measured values
...	Forces you to name remaining arguments
return_lik	If yes, it returns a list with lik and glik
ys	Supplementary output data
Xs	Supplementary input data
HandlingSuppData	How should supplementary data be handled? * Correct: full likelihood with grid and supplemental data * Only: only use supplemental data * Ignore: ignore supplemental data

Value

Vector for gradient of likelihood w.r.t. x (theta)

Examples

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)

CGGP documentation built on May 8, 2021, 5:06 p.m.