GmultiInhom | R Documentation |
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.
GmultiInhom(X, I, J, lambda = NULL, lambdaI = NULL, lambdaJ = NULL, lambdamin = NULL, ..., r = NULL, ReferenceMeasureMarkSetI = NULL, ratio = FALSE)
X |
A spatial point pattern (object of class |
I |
A subset index specifying the subset of points from which
distances are measured. Any kind of subset index acceptable
to |
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 |
lambdaI |
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 |
... |
Ignored. |
r |
Vector of distance values at which the inhomogeneous G function should be estimated. There is a sensible default. |
ReferenceMeasureMarkSetI |
Optional. The total measure of the mark set. A positive number. |
ratio |
Logical value indicating whether to save ratio information. |
See Cronie and Van Lieshout (2015).
Object of class "fv"
containing the estimate of the
inhomogeneous multitype G 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
Ginhom
,
Gmulti
X <- rescale(amacrine) I <- (marks(X) == "on") J <- (marks(X) == "off") mod <- ppm(X ~ marks * x) lam <- fitted(mod, dataonly=TRUE) lmin <- min(predict(mod)[["off"]]) * 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="")
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