`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)`

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`

.

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.

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` . |