rgauss: rgauss function

In lgcp: Log-Gaussian Cox Process

rgauss function

Description

A function to simulate a Gaussian field on a regular square lattice, the returned object is of class lgcpgrid.

Usage

rgauss(
  n = 1,
  range = c(0, 1),
  ncells = 128,
  spatial.covmodel = "exponential",
  model.parameters = lgcppars(sigma = 2, phi = 0.1),
  covpars = c(),
  ext = 2
)

Arguments

n	the number of realisations to generate. Default is 1.
range	a vector of length 2, defining the left-most and right most cell centroids in the x-direction. Note that the centroids in the y-direction are the same as those in the x-direction.
ncells	the number of cells, typially a power of 2
spatial.covmodel	spatial covariance function, default is exponential, see ?CovarianceFct
model.parameters	parameters of model, see ?lgcppars. Only set sigma and phi for spatial model.
covpars	vector of additional parameters for spatial covariance function, in order they appear in chosen model in ?CovarianceFct
ext	how much to extend the parameter space by. Default is 2.

Value

an lgcp grid object containing the simulated field(s).

lgcp documentation built on Oct. 3, 2023, 5:08 p.m.