RandomFields (version 3.1.16)

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.

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