Overview over classes of RMmodels
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. |
Martin Schlather, schlather@math.uni-mannheim.de, https://www.wim.uni-mannheim.de/schlather/
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.RdPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.