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Estimates the inhomogeneous multitype pair correlation function
(from type
pcfdot.inhom(X, i, lambdaI = NULL, lambdadot = NULL, ...,
r = NULL, breaks = NULL,
kernel="epanechnikov", bw=NULL, stoyan=0.15,
correction = c("isotropic", "Ripley", "translate"),
sigma = NULL, varcov = NULL)
The observed point pattern,
from which an estimate of the inhomogeneous
multitype pair correlation function
The type (mark value)
of the points in X
from which distances are measured.
A character string (or something that will be converted to a
character string).
Defaults to the first level of marks(X)
.
Optional.
Values of the estimated intensity function of the points of type i
.
Either a vector giving the intensity values
at the points of type i
,
a pixel image (object of class "im"
) giving the
intensity values at all locations, or a function(x,y)
which
can be evaluated to give the intensity value at any location.
Optional.
Values of the estimated intensity function of the point pattern X
.
A numeric vector, pixel image or function(x,y)
.
Vector of values for the argument
This argument is for internal use only.
Choice of smoothing kernel, passed to density.default
.
Bandwidth for smoothing kernel, passed to density.default
.
Other arguments passed to the kernel density estimation
function density.default
.
Bandwidth coefficient; see Details.
Choice of edge correction.
Optional arguments passed to density.ppp
to control the smoothing bandwidth, when lambdaI
or
lambdadot
is estimated by kernel smoothing.
A function value table (object of class "fv"
).
Essentially a data frame containing the variables
the vector of values of the argument
vector of values equal to 1,
the theoretical value of
vector of values of
vector of values of
The inhomogeneous multitype (type
The best intuitive interpretation is the following: the probability
The command pcfdot.inhom
estimates the inhomogeneous
multitype pair correlation using a modified version of
the algorithm in pcf.ppp
.
If the arguments lambdaI
and lambdadot
are missing or
null, they are estimated from X
by kernel smoothing using a
leave-one-out estimator.
# NOT RUN {
data(amacrine)
plot(pcfdot.inhom(amacrine, "on", stoyan=0.1), legendpos="bottom")
# }
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