R: Space-time Covariance Models

RMmodelsSpacetime {RandomFields} | R Documentation

## Space-time Covariance Models

### Description

Here, a collection of implemented space-time models is given.

### Details

Stationary space-time models

Here, most of the models are composed models (operators). Note that in space-time modelling the argument `proj` may take also the values `"space"` for the projection on the space and `"time"` for the projection onto the time axis.

separable models | are easily constructed using `+`, `*`, and proj, see also the example below
`RMave` | space-time moving average model
`RMcoxisham` | Cox-Isham model
`RMcurlfree` | curlfree (spatial) field (stationary and anisotropic)
`RMdivfree` | divergence free (spatial) vector valued field, (stationary and anisotropic)
`RMgennsst` | generalization of Gneiting's non-separable space-time model
`RMiaco` | non-separabel space-time model
`RMmastein` | Ma-Stein model
`RMnsst` | Gneiting's non-separable space-time model
`RMstein` | Stein's non-separabel space-time model
`RMstp` | Single temporal process
`RMtbm` | Turning bands operator

### Author(s)

Alexander Malinowski, malinowski@math.uni-mannheim.de

Martin Schlather, schlather@math.uni-mannheim.de

### References

- Schlather, M. (2011) Construction of covariance functions and unconditional simulation of random fields. In Porcu, E., Montero, J.M. and Schlather, M., Space-Time Processes and Challenges Related to Environmental Problems. New York: Springer.

### See Also

`RFformula`, RM, `RMmodels`, `RMmodelsAdvanced`

### Examples

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

    ## separable model with expontential model in space and gaussian in time
    model <- RMexp(proj = "space") * RMgauss(proj = "time")
    xT <- seq(0, 10, 0.1)
    z <- RFsimulate(model, x=xT, T=xT)
    plot(z)

[Package RandomFields version 3.1.50 Index]