R: Gaussian Determinantal Point Process Model

dppGauss {spatstat.core} | R Documentation

## Gaussian Determinantal Point Process Model

### Description

Function generating an instance of the Gaussian determinantal point process model.

### Usage

    dppGauss(...)

### Arguments

`...` | arguments of the form `tag=value` specifying the parameters. See Details.

### Details

The Gaussian DPP is defined in (Lavancier, Moller and Rubak, 2015) The possible parameters are:

- the intensity `lambda` as a positive numeric

- the scale parameter `alpha` as a positive numeric

- the dimension `d` as a positive integer

### Value

An object of class `"detpointprocfamily"`.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au

Rolf Turner r.turner@auckland.ac.nz

and Ege Rubak rubak@math.aau.dk

### References

Lavancier, F. Moller, J. and Rubak, E. (2015) Determinantal point process models and statistical inference Journal of the Royal Statistical Society, Series B 77, 853–977.

### See Also

`dppBessel`, `dppCauchy`, `dppMatern`, `dppPowerExp`

### Examples

    m <- dppGauss(lambda=100, alpha=.05, d=2)

[Package spatstat.core version 2.3-1 Index]