FmultiInhom {spatstat.explore} | R Documentation |
Inhomogeneous Marked F-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 fixed point to the nearest point in subset
,
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)
Arguments
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 |
Details
See Cronie and Van Lieshout (2015).
The functions FmultiInhom
and Fmulti.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 <- 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))