View source: R/pcfmulti.inhom.R
pcfcross.inhom | R Documentation |
Estimates the inhomogeneous cross-type pair correlation function for a multitype point pattern.
pcfcross.inhom(X, i, j, lambdaI = NULL, lambdaJ = NULL, ...,
r = NULL, breaks = NULL,
kernel="epanechnikov", bw=NULL, adjust.bw = 1, stoyan=0.15,
correction = c("isotropic", "Ripley", "translate"),
sigma = NULL, adjust.sigma = 1, varcov = NULL)
X |
The observed point pattern,
from which an estimate of the inhomogeneous
cross-type pair correlation function
|
i |
The type (mark value)
of the points in |
j |
The type (mark value)
of the points in |
lambdaI |
Optional.
Values of the estimated intensity function of the points of type |
lambdaJ |
Optional.
Values of the estimated intensity function of the points of type |
r |
Vector of values for the argument |
breaks |
This argument is for internal use only. |
kernel |
Choice of one-dimensional smoothing kernel,
passed to |
bw |
Bandwidth for one-dimensional smoothing kernel,
passed to |
adjust.bw |
Numeric value. |
... |
Other arguments passed to the one-dimensional kernel density estimation
function |
stoyan |
Bandwidth coefficient; see Details. |
correction |
Choice of edge correction. |
sigma , varcov |
Optional arguments passed to |
adjust.sigma |
Numeric value. |
The inhomogeneous cross-type pair correlation function
g_{ij}(r)
is a summary of the dependence between two types of points in a
multitype spatial point process that does not have a uniform
density of points.
The best intuitive interpretation is the following: the probability
p(r)
of finding two points, of types i
and j
respectively, at locations x
and y
separated by a distance r
is equal to
p(r) = \lambda_i(x) lambda_j(y) g(r) \,{\rm d}x \, {\rm d}y
where \lambda_i
is the intensity function
of the process of points of type i
.
For a multitype Poisson point process,
this probability is
p(r) = \lambda_i(x) \lambda_j(y)
so g_{ij}(r) = 1
.
The command pcfcross.inhom
estimates the inhomogeneous
pair correlation using a modified version of
the algorithm in pcf.ppp
.
The arguments bw
and adjust.bw
control the
degree of one-dimensional smoothing of the estimate of pair correlation.
If the arguments lambdaI
and/or lambdaJ
are missing or
null, they will be estimated from X
by spatial kernel smoothing
using a leave-one-out estimator, computed by density.ppp
.
The arguments sigma
, varcov
and adjust.sigma
control the degree of spatial smoothing.
A function value table (object of class "fv"
).
Essentially a data frame containing the variables
r |
the vector of values of the argument |
theo |
vector of values equal to 1,
the theoretical value of |
trans |
vector of values of |
iso |
vector of values of |
as required.
and \rolf
pcf.ppp
,
pcfinhom
,
pcfcross
,
pcfdot.inhom
plot(pcfcross.inhom(amacrine, "on", "off", stoyan=0.1),
legendpos="bottom")
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