CGGPcreate {CGGP}

Create sparse grid GP

Description

Create sparse grid GP

Usage

CGGPcreate(
  d,
  batchsize,
  corr = "PowerExponential",
  grid_sizes = c(1, 2, 4, 4, 8, 12, 20, 28, 32),
  Xs = NULL,
  Ys = NULL,
  HandlingSuppData = "Correct",
  supp_args = list()
)

Arguments

d

Input dimension

batchsize

Number added to design each batch for now only on predictions

corr

Name of correlation function to use. Must be one of "CauchySQT", "CauchySQ", "Cauchy", "Gaussian", "PowerExp", "Matern32", "Matern52".

grid_sizes

Size of grid refinements.

Xs

Supplemental X data

Ys

Supplemental Y 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

supp_args

Arguments used to fit if Xs and Ys are given

Value

CGGP

See Also

Other CGGP core functions: CGGPappend(), CGGPfit(), predict.CGGP()

Examples

CGGPcreate(d=8,200)