RM: Overview over classes of 'RMmodels'
In RandomFields: Simulation and Analysis of Random Fields

Description Man pages See Also Examples

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

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
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 are typically used to build non-stationary covariance models and arbitrary trends
RMmodelsAuxiliary	rather specialized models, most of them not having positive definiteness property, but used internally in certain simulation algorithms, for instance.

RC, RR, RF, R.

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