`kmNuggets.init`

is used to give initial values to fit kriging models, in presence of noisy observations.

`kmNuggets.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 give a first estimation of the process variance, as well as lower and upper bounds. |

2) | Simulate several values for the process variance, around the estimation 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). |