R: Fitting Kriging Models

kmNoNugget.init {DiceKriging} | R Documentation

## Fitting Kriging Models

### 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`

[Package DiceKriging version 1.5.8 Index]