`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`

.

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 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). |