spatstat.explore (version 3.3-1)

FmultiInhom: Inhomogeneous Marked F-Function

Description

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

Usage

Fmulti.inhom(X, J,
              lambda = NULL, lambdaJ = NULL, lambdamin = NULL,
              ...,
              r = NULL)
  FmultiInhom(X, J,
              lambda = NULL, lambdaJ = NULL, lambdamin = NULL,
              ...,
              r = NULL)

Value

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

Arguments

X

A spatial point pattern (object of class "ppp".

J

A subset index specifying the subset of points to which distances are measured. Any kind of subset index acceptable to [.ppp.

lambda

Intensity estimates for each point of X. A numeric vector of length equal to npoints(X). Incompatible with lambdaJ.

lambdaJ

Intensity estimates for each point of X[J]. A numeric vector of length equal to npoints(X[J]). Incompatible with lambda.

lambdamin

A lower bound for the intensity, or at least a lower bound for the values in lambdaJ or lambda[J].

...

Extra arguments passed to as.mask to control the pixel resolution for the computation.

r

Vector of distance values at which the inhomogeneous \(G\) function should be estimated. There is a sensible default.

Author

Ottmar Cronie and Marie-Colette van Lieshout. Rewritten for spatstat by Adrian Baddeley .

Details

See Cronie and Van Lieshout (2015).

The functions FmultiInhom and Fmulti.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

Finhom

Examples

  X <- amacrine
  J <- (marks(X) == "off")
  online <- interactive()
  eps <- if(online) NULL else 0.025
  if(online && require(spatstat.model)) {
    mod <- ppm(X ~ marks * x, eps=eps)
    lambdaX <- fitted(mod, dataonly=TRUE)
    lambdaOff <- predict(mod, eps=eps)[["off"]]
    lmin <- min(lambdaOff) * 0.9
  } else {
    ## faster computation for package checker only
    lambdaX <- intensity(X)[as.integer(marks(X))]
    lmin <- intensity(X)[2] * 0.9
  }

  plot(FmultiInhom(X, J, lambda=lambdaX, lambdamin=lmin, eps=eps))