CGGP (version 1.0.1)

CGGPfit: Update CGGP model given data

Description

This function will update the GP parameters for a CGGP design.

Usage

CGGPfit(CGGP, Y, Xs = NULL, Ys = NULL,
  theta0 = pmax(pmin(CGGP$thetaMAP, 0.8), -0.8),
  HandlingSuppData = CGGP$HandlingSuppData,
  separateoutputparameterdimensions = is.matrix(CGGP$thetaMAP),
  set_thetaMAP_to, corr, Ynew)

Arguments

CGGP

Sparse grid objects

Y

Output values calculated at CGGP$design

Xs

Supplemental X matrix

Ys

Supplemental Y values

theta0

Initial theta

HandlingSuppData

How should supplementary data be handled? * Correct: full likelihood with grid and supplemental data * Only: only use supplemental data * Ignore: ignore supplemental data

separateoutputparameterdimensions

If multiple output dimensions, should separate parameters be fit to each dimension?

set_thetaMAP_to

Value for thetaMAP to be set to

corr

Will update correlation function, if left missing it will be same as last time.

Ynew

Values of `CGGP$design_unevaluated`

Value

Updated CGGP object fit to data given

See Also

Other CGGP core functions: CGGPappend, CGGPcreate, predict.CGGP

Examples

# NOT RUN {
cg <- CGGPcreate(d=3, batchsize=100)
y <- apply(cg$design, 1, function(x){x[1]+x[2]^2})
cg <- CGGPfit(CGGP=cg, Y=y)
# }