spatstat.explore (version 3.7-0)

GmultiInhom: Inhomogeneous Marked G-Function

Description

For a marked point pattern, estimate the inhomogeneous version of the multitype \(G\) function, effectively the cumulative distribution function of the distance from a point in subset \(I\) to the nearest point in subset \(J\), adjusted for spatially varying intensity.

Usage

Gmulti.inhom(X, I, J,
             lambda = NULL, lambdaI = NULL, lambdaJ = NULL,
             lambdamin = NULL, ...,
             r = NULL, rmax=NULL,
             ReferenceMeasureMarkSetI = NULL,
             ratio = FALSE)
  GmultiInhom(X, I, J,
             lambda = NULL, lambdaI = NULL, lambdaJ = NULL,
             lambdamin = NULL, ...,
             r = NULL, rmax=NULL, 
             ReferenceMeasureMarkSetI = NULL,
             ratio = FALSE)

Value

Object of class "fv" containing the estimate of the inhomogeneous multitype \(G\) function.

Details

See Cronie and Van Lieshout (2015).

The functions GmultiInhom and Gmulti.inhom are identical.

References

Cronie, O. and Van Lieshout, M.N.M. (2015) Summary statistics for inhomogeneous marked point processes. Annals of the Institute of Statistical Mathematics DOI: 10.1007/s10463-015-0515-z

See Also

Ginhom, Gmulti

Examples

  X <- rescale(amacrine)
  I <- (marks(X) == "on")
  J <- (marks(X) == "off")
  if(interactive() && require(spatstat.model)) {
    ## how to do it normally
    mod <- ppm(X ~ marks * x)
    lam <- fitted(mod, dataonly=TRUE)
    lmin <- min(predict(mod)[["off"]]) * 0.9
  } else {
    ## for package testing
    lam <- intensity(X)[as.integer(marks(X))]
    lmin <- intensity(X)[2] * 0.9
  }
  plot(GmultiInhom(X, I, J, lambda=lam, lambdamin=lmin))
  # equivalent
  plot(GmultiInhom(X, I, J, lambdaI=lam[I], lambdaJ=lam[J], lambdamin=lmin),
       main="")