km1Nugget.init {DiceKriging} | R Documentation |
km1Nugget.init
is used to give good initial values to fit kriging models when there is an unknown nugget effect to be estimated.
km1Nugget.init(model)
model |
an object of class km . |
The procedure can be summarized in 4 stages :
1) | Compute the variogram and deduce a first estimation of the total variance. If an initial value is provided for nugget , check its compatibility with the estimated variance. If not, use again the variogram to give a first estimation of the nugget effect. |
2) | Simulate several values for the nugget effect and the process variance, around the estimations obtained at stage 1). The number of simulations is the one given in model@control$pop.size . |
3) | If no initial value is provided for the other covariance parameters, simulate them uniformly inside the domain delimited by model@lower and model@upper . The number of simulations is the same as in stage 2). |
4) | Compute the likelihood at each simulated "point" (variance + nugget effect + other covariance parameters), and take the best one. This point gives the first initial values. |
An object of class km
.
O. Roustant, David Ginsbourger, Ecole des Mines de St-Etienne.