RFcrossvalidate: Fitting model parameters to spatial data (regionalised...

In RandomFields: Simulation and Analysis of Random Fields

Description

The function estimates arbitrary parameters of a random field specification with various methods. Currently, the models to be fitted can be

• Gaussian random fields

• linear models

The fitting of max-stable random fields and others has not been implemented yet.

Usage

RFcrossvalidate(model, x, y=NULL, z=NULL, T=NULL, grid=NULL, data,
                params, lower=NULL, upper=NULL, method="ml",
                users.guess=NULL, distances=NULL, dim, optim.control=NULL,
                transform=NULL, full = FALSE, ...)

Arguments

model,params	\argModel
x	\argX
y,z	\argYz
T	\argT
grid	\argGrid
data	\argData
lower	\argLower
upper	\argUpper
method	Single method to be used for estimating, either one of the methods or one of the sub.methods see RFfit
users.guess	\argUsersguess
distances,dim	\argDistances
optim.control	\argOptimcontrol
transform	\argTransform
full	logical. If TRUE then cross-validation is also performed for intermediate models used in RFfit (if any).
...	\argDots

Value

An object of the class "RFcrossvalidate" which is a list with the following components, cf. xvalid in the package geoR :

data	the original data.
predicted	the values predicted by cross-validation.
krige.var	the cross-validation prediction variance.
error	the differences data - predicted value.
std.error	the errors divided by the square root of the prediction variances.
p	In contrast to geoR the p-value is returned, i.e. the probability that a difference with absolute value larger than the absolute value of the actual difference is observed. A method for summary returns summary statistics for the errors and standard errors similar to geoR. If cross_refit = TRUE and detailed_output = TRUE the returned object also contains a fitted which is a list of fitted models.

Methods

print

prints the summary

summary

gives a summary

Note

An important option is cross_refit that determines whether the model is refitted for each location left out. Default is FALSE. See also RFoptions.

Note

This function does not depend on the value of RFoptions()$PracticalRange. The function RFcrossvalidate always uses the standard specification of the covariance model as given in RMmodel.

References

• Ribeiro, P.J., Jr. and Diggle, P.J (2014) R package geoR.

• Burnham, K. P. and Anderson, D. R. (2002) Model selection and Multi-Model Inference: A Practical Information-Theoretic Approach. 2nd edition. New York: Springer.

See Also

RFratiotest RFfit RMmodel, RandomFields, weather.

Examples

RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
##                   RFoptions(seed=NA) to make them all random again




## currently disabled!

RandomFields documentation built on Jan. 19, 2022, 1:06 a.m.