CEGO (version 2.0.0)

modelKrigingLikelihood: Calculate negative log-likelihood

Description

Used to determine theta/lambda/p values for the Kriging model in modelKriging with Maximum Likelihood Estimation (MLE).

Usage

modelKrigingLikelihood(xt, dX, y, optimizeP = FALSE, useLambda = FALSE,
  corr = fcorrGauss)

Arguments

xt

vector, containing log10(theta), p and lambda

dX

matrix of distances/dissimilarites between training samples

y

vector of observations at sample locations

optimizeP

whether to optimize p or not (FALSE at default)

useLambda

whether to use nugget effect, i.e., lambda (FALSE at default)

corr

whether to use nugget effect, i.e., lambda (fcorrGauss at default)

Value

• list with elements NegLnLike concentrated log-likelihood *-1 for minimising Psi correlation matrix Psinv inverse of correlation matrix (to save computation time in forrRegPredictor) mu MLE of model parameter mu yMu vector of observations y minus mu SSQ MLE of model parameter sigma^2

See Also

modelKriging