| FmultiInhom | R Documentation | 
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.
  Fmulti.inhom(X, J,
              lambda = NULL, lambdaJ = NULL, lambdamin = NULL,
              ...,
              r = NULL)
  FmultiInhom(X, J,
              lambda = NULL, lambdaJ = NULL, lambdamin = NULL,
              ...,
              r = NULL)
X | 
 A spatial point pattern (object of class   | 
J | 
 A subset index specifying the subset of points to which
distances are measured. Any kind of subset index acceptable
to   | 
lambda | 
 Intensity estimates for each point of   | 
lambdaJ | 
 Intensity estimates for each point of   | 
lambdamin | 
 A lower bound for the intensity,
or at least a lower bound for the values in   | 
... | 
 Extra arguments passed to   | 
r | 
 Vector of distance values at which the inhomogeneous   | 
See Cronie and Van Lieshout (2015).
The functions FmultiInhom and Fmulti.inhom are identical.
Object of class "fv" containing the estimate of the
inhomogeneous multitype F function.
Ottmar Cronie and Marie-Colette van Lieshout. Rewritten for spatstat by \adrian.
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
Finhom
  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))
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