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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