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dppGauss

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)

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

Examples

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

spatstat.core

Core Functionality of the 'spatstat' Family

v2.1-2
GPL (>= 2)
Authors
Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut], Kasper Klitgaard Berthelsen [ctb], Achmad Choiruddin [ctb], Jean-Francois Coeurjolly [ctb], Ottmar Cronie [ctb], Tilman Davies [ctb], Julian Gilbey [ctb], Yongtao Guan [ctb], Ute Hahn [ctb], Kassel Hingee [ctb], Abdollah Jalilian [ctb], Marie-Colette van Lieshout [ctb], Greg McSwiggan [ctb], Tuomas Rajala [ctb], Suman Rakshit [ctb], Dominic Schuhmacher [ctb], Rasmus Plenge Waagepetersen [ctb], Hangsheng Wang [ctb]
Initial release
2021-04-17

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