kmNoNugget.init: Fitting Kriging Models

In DiceKriging: Kriging Methods for Computer Experiments

Description

kmNoNugget.init is used to give initial values to fit kriging models when there is no nugget effect nor noisy observations.

Usage

kmNoNugget.init(model, fn, fnscale)

Arguments

model	an object of class km.
fn	the function considered: logLikFun or leaveOneOutFun.
fnscale	a real number which sign determines the direction for optimization: <0 for logLikFun, >0 for leaveOneOutFun.

Details

The procedure can be summarized in 2 stages:

1)	If no initial value is provided by the user for the covariance parameters, simulate them uniformly inside the domain delimited by model@lower and model@upper. The number of simulations is the one given in model@control$pop.size.
2)	Compute the likelihood for each parameters set, and select the one(s) that gives the highest value(s). The number of values considered can be set by the argument multistart in km.

Value

par	a matrix whose rows contain initial vectors of parameters.
value	a vector containing the function values corresponding to par.
cov	a list containing the covariance objects corresponding to par.
lower	,
upper	vectors containing lower and upper bounds for parameters.

Author(s)

O. Roustant, David Ginsbourger, Ecole des Mines de St-Etienne.

See Also

km, kmEstimate

DiceKriging documentation built on Feb. 24, 2021, 1:07 a.m.