Functions to compute and plot summary statistics of prediction errors to (cross-)validate fitted spatial linear models by the criteria proposed by Gneiting et al. (2007) for assessing probabilistic forecasts.
An object of class georob as returned by georob and representing a (robustly) fitted spatial linear model. Objects of this class have methods for model building (see georobModelBuilding) and cross-validation (see cv.georob), for computing (robust) kriging predictions (see predict.georob), for plotting (see plot.georob) and for common generic functions (see georobMethods).
This page documents parameters used to control georob. It describes the arguments of the functions control.georob, param.transf, fwd.transf, dfwd.transf, bwd.transf, control.rq, control.nleqslv, control.nlminb and control.optim, which all serve to control the behaviour of georob.
predict.georob
(Package: georob) :
Predict Method for Robustly Fitted Spatial Linear Models
Robust and customary external drift kriging prediction based on a spatial linear models fitted by georob. The predict method for the class georob computes fitted values, point and block kriging predictions as well as model terms for display by termplot.
default.aniso
(Package: georob) :
Setting Default Values of Variogram Parameters
Helper functions to set sensible default values for anisotropy parameters and for controlling what variogram and anisotropy parameters should be estimated.
This page documents the functions pmm for parallelized matrix multiplication and the function control.pmm, which controls the behaviour of pmm and other functions that execute tasks in parallel.
cv.georob
(Package: georob) :
Cross-Validating a Spatial Linear Model Fitted by code{georob
This function assesses the goodness-of-fit of a spatial linear model by K-fold cross-validation. In more detail, the model is re-fitted K times by robust (or Gaussian) (RE)ML, excluding each time 1/Kth of the data. The re-fitted models are used to compute robust (or customary) external kriging predictions for the omitted observations. If the response variable is log-transformed then the kriging predictions can be optionally transformed back to the orginal scale of the measurements. S3methods for evaluating and plotting diagnostic summaries of the cross-validation errors are decribed for the function validate.predictions.
providing 
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