R: Overview over classes of 'RMmodels'

RMmodels Overview {RandomFields} | R Documentation

## Overview over classes of `RMmodels`

### Description

Various classes of models `RMxxx` are implemented in RandomFields, that have their own man pages. Here an overview over these man pages are given

### Man pages

Beginners should start with RMmodels, then go for RMmodelsAdvanced if more information is needed.

RMmodels | general introduction and a collection of simple models
RMmodelsAdvanced | includes more advanced stationary and isotropic models, variogram models, non-stationary models and trend models
Bayesian | hierarchical models
RMmodelsMultivariate | multivariate covariance models and multivariate trend models
RMmodelsNonstationary | non-stationary covariance models
RMmodelsMultivariate | multivariate covariance models and multivariate trend models
RMmodelsSpaceTime | space-time covariance models
Spherical models | models based on the polar coordinate system, usually used in earth models
Tail correlation functions | models related to max-stable random fields
trend modelling | how to pass trend specifications
Mathematical functions | simple mathematical functions that typically used to build non-stationary covariance models and arbitrary trends
RMmodelsAuxiliary | rather specialised models, most of them not having positive definiteness property, but used internally in certain simulation algorithms, for instance.

### Author(s)

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

### See Also

RC, RR RF, R.

### Examples

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

    RFgetModelNames(type="positive definite", domain="single variable",
                    isotropy="isotropic", operator=!FALSE) ## RMmodel.Rd

[Package RandomFields version 3.1.50 Index]