RandomFields (version 3.1.12)

RMmodels Overview: 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. ll{ 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. }

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


FinalizeExample()