Description Usage Arguments Details Value Author(s) Examples

Jacobian of mean values of statistics

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`models` |
object of class |

`points` |
matrix or list of points to predict the sample means of statistics |

`Xs` |
matrix of sample points |

`data` |
data frame of sample means of statistics at sampled points |

`krig.type` |
name of kriging type, either " |

The function can be used to predict any values by kriging given a covariance model. Each covariance model is given as an
element of the list '`models`

' including its own trend model and covariance function name. There are two types of kriging predictors
available. First, the *dual kriging* predictor, set by '`krig.type`

'="`dual`

" or the one based on the calculation of prediction
variances, setting '`krig.type`

' to "`var`

". Both types result in exactly the same predicted values and only differ by whether or not
kriging variances should be computed. The data, e. g. sample means of each statistic, must be given as column vectors where each row corresponds
to a sample point in the data frame given in the argument '`data`

'.

The function '`jacobian`

' computes the partial derivatives of sample means of the statistics
as columns and for each component of the parameter vector as rows by forward difference approximations.

`estim` |
list of predicted values of sample means of statistics (including prediction
variances if ' |

`jacobian` |
list of Jacobians at predicted values of sample means of statistics |

M. Baaske

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