Jmulti.inhom | R Documentation |
For a marked point pattern,
estimate the inhomogeneous version of the multitype J
function.
Jmulti.inhom(X, I, J,
lambda = NULL, lambdaI = NULL, lambdaJ = NULL,
lambdamin = NULL,
...,
r = NULL,
ReferenceMeasureMarkSetI = NULL,
ratio = FALSE)
X |
The observed point pattern,
from which an estimate of the inhomogeneous multitype |
I |
Subset index specifying the points of |
J |
Subset index specifying the points in |
lambda |
Optional.
Values of the estimated intensity function.
Either a vector giving the intensity values
at the points of the pattern |
lambdaI |
Optional.
Values of the estimated intensity of the sub-process |
lambdaJ |
Optional.
Values of the estimated intensity of the sub-process |
lambdamin |
Optional. The minimum possible value of the intensity over the spatial domain. A positive numerical value. |
... |
Extra arguments passed to |
r |
vector of values for the argument |
ReferenceMeasureMarkSetI |
Optional. The total measure of the mark set. A positive number. |
ratio |
Logical value indicating whether to save ratio information. |
This function is the counterpart of Jmulti
for inhomogeneous patterns. It is computed by evaluating the
inhomogeneous G
function GmultiInhom
and the inhomogeneous F
function FmultiInhom
and computing the ratio J = (1-G)/(1-F)
.
Object of class "fv"
containing the estimate of the
inhomogeneous multitype J
function.
Jonatan \Gonzalez and \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
Jcross.inhom
, Jdot.inhom
for special cases.
GmultiInhom
, FmultiInhom
,
Jmulti
.
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
dd <- NULL
} else {
## for package testing
lam <- intensity(X)[as.integer(marks(X))]
lmin <- intensity(X)[2] * 0.9
dd <- 32
}
JM <- Jmulti.inhom(X, I, J, lambda=lam, lambdamin=lmin, dimyx=dd)
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