kmNoNugget.init is used to give initial values to fit kriging models when there is no nugget effect nor noisy observations.
kmNoNugget.init(model, fn, fnscale)
a matrix whose rows contain initial vectors of parameters.
a vector containing the function values corresponding to par.
a list containing the covariance objects corresponding to par.
,
vectors containing lower and upper bounds for parameters.
an object of class km.
the function considered: logLikFun or leaveOneOutFun.
a real number which sign determines the direction for optimization: <0 for logLikFun, >0 for leaveOneOutFun.
O. Roustant, David Ginsbourger, Ecole des Mines de St-Etienne.
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. |
km, kmEstimate