Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

RPt

Simulation of T Random Fields

Description

RPt defines a t field.

Usage

RPt(phi, boxcox, nu)

Arguments

phi

the RMmodel. If a model for the distribution is not specified, RPgauss is used as default and a covariance model is expected.
boxcox

the one or two parameters of the box cox transformation. If not given, the globally defined parameters are used. See RFboxcox for details.

nu

non-negative number. Degree of freedom.

Value

The function returns an object of class RMmodel.

Author(s)

References

Related to the extremal t process

  • T. Opitz (2012) A spectral construction of the extremal t process. arxiv 1207.2296.

See Also

Examples

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

model <- RPt(RMexp(), nu=2)
x <- seq(0, 10, 0.1)
z <- RFsimulate(model, x, x, n=4)
plot(z)
RandomFields

Simulation and Analysis of Random Fields

v3.3.10
GPL (>= 3)
Authors
Martin Schlather [aut, cre], Alexander Malinowski [aut], Marco Oesting [aut], Daphne Boecker [aut], Kirstin Strokorb [aut], Sebastian Engelke [aut], Johannes Martini [aut], Felix Ballani [aut], Olga Moreva [aut], Jonas Auel[ctr], Peter Menck [ctr], Sebastian Gross [ctr], Ulrike Ober [ctb], Paulo Ribeiro [ctb], Brian D. Ripley [ctb], Richard Singleton [ctb], Ben Pfaff [ctb], R Core Team [ctb]
Initial release

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.