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

RFcrossvalidate {RandomFields} | R Documentation

## Fitting model parameters to spatial data (regionalised variables) and to linear (mixed) models

### Description

The function estimates arbitrary parameters of a random field specification with various methods. Currenty, the model 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,
     lower = NULL, upper = NULL, method="ml",
     users.guess = NULL,
     distances = NULL, dim, optim.control = NULL,transform = NULL,
     full = FALSE, ...)

### Arguments

`model, x, y, z, T, grid, data,lower, upper, users.guess, distances, dim, optim.control, transform, ...` | see `RFfit`
`method` | Single method to be used for estimating, either one of the `methods` or one of the `sub.methods` see `RFfit`
`full` | logical. if `TRUE` then crossvalidatiaon is also performed for intermediate models used in `RFfit` (if any).

### 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 constains 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`.

### Author(s)

Martin Schlather, schlather@math.uni-mannheim.de http://ms.math.uni-mannheim.de/de/publications/software

### 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!

[Package RandomFields version 3.1.50 Index]