R: Simulation based on circulant embedding

krigeSimCE {gstat} | R Documentation

## Simulation based on circulant embedding

### Description

Simulating a conditional/unconditional Gaussian random field via kriging and circulant embedding

### Usage

    krigeSimCE(formula, data, newdata, model, n = 1, ext = 2)

### Arguments

`formula` | the formula of the kriging predictor
`data` | spatial data frame that conditions the simulation
`newdata` | locations in space where the Gaussian random field shall be simulated
`model` | a vgm model that defines the spatial covariance structure
`n` | number of simulations
`ext` | extension factor of the circulant embedding, defaults to 2

### Value

A spatial data frame as defined in `newdata` with `n` simulations.

### Author(s)

Benedikt Graeler

### References

Davies, Tilman M., and David Bryant: "On circulant embedding for Gaussian random fields in R." Journal of Statistical Software 55.9 (2013): 1-21. See i.e. the supplementary files at (retrieved 2018-05-25): https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v055i09/v55i09.R

### See Also

`krigeSTSimTB`

### Examples

    # see demo('circEmbeddingMeuse')

[Package gstat version 2.0-3 Index]