GmultiInhom {spatstat.explore} | R Documentation |
Inhomogeneous Marked G-Function
Description
For a marked point pattern,
estimate the inhomogeneous version of the multitype function,
effectively the cumulative distribution function of the distance from
a point in subset
to the nearest point in subset
,
adjusted for spatially varying intensity.
Usage
Gmulti.inhom(X, I, J,
lambda = NULL, lambdaI = NULL, lambdaJ = NULL,
lambdamin = NULL, ...,
r = NULL,
ReferenceMeasureMarkSetI = NULL,
ratio = FALSE)
GmultiInhom(X, I, J,
lambda = NULL, lambdaI = NULL, lambdaJ = NULL,
lambdamin = NULL, ...,
r = NULL,
ReferenceMeasureMarkSetI = NULL,
ratio = FALSE)
Arguments
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 |
ReferenceMeasureMarkSetI |
Optional. The total measure of the mark set. A positive number. |
ratio |
Logical value indicating whether to save ratio information. |
Details
See Cronie and Van Lieshout (2015).
The functions GmultiInhom
and Gmulti.inhom
are identical.
Value
Object of class "fv"
containing the estimate of the
inhomogeneous multitype function.
Author(s)
Ottmar Cronie and Marie-Colette van Lieshout. Rewritten for spatstat by Adrian Baddeley Adrian.Baddeley@curtin.edu.au.
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
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="")