lgcpSimSpatialCovariates: lgcpSimSpatialCovariates function
In bentaylor1/lgcp: Log-Gaussian Cox Process

A function to simulate a spatial LGCP.

lgcpSimSpatialCovariates(formula, owin, regionalcovariates = NULL,
  pixelcovariates = NULL, Zmat = NULL, beta, poisson.offset = NULL,
  cellwidth, model.parameters, spatial.covmodel = "exponential",
  covpars = c(), ext = 2, plot = FALSE, inclusion = "touching")

`formula`	a formula of the form X ~ var1 + var2 etc.
`owin`	the observation window on which to do the simulation
`regionalcovariates`	an optional object of class SpatialPolygonsDataFrame containing covariates
`pixelcovariates`	an optional object of class SpatialPixelsDataFrame containing covariates
`Zmat`	optional design matrix, if the polygon/polygon overlays have already been computed
`beta`	the parameters, beta for the model
`poisson.offset`	the poisson offet, created using a SpatialAtRisk.fromXYZ class of objects
`cellwidth`	the with of cells on which to do the simulation
`model.parameters`	the paramters of the model eg list(sigma=1,phi=0.2)
`spatial.covmodel`	the choice of spatial covariance model, can be anything from the RandomFields covariance function, CovariacenFct.
`covpars`	additional covariance parameters, for the chosen model, optional.
`ext`	the amount by which to extend the observation grid in each direction, default is 2
`plot`	whether to plot the resulting data
`inclusion`	criterion for cells being included into observation window. Either 'touching' or 'centroid'. The former, the default, includes all cells that touch the observation window, the latter includes all cells whose centroids are inside the observation window.