localKinhom | R Documentation |
Computes spatially-weighted versions of the
the local K
-function or L
-function.
localKinhom(X, lambda, ..., rmax = NULL,
correction = "Ripley", verbose = TRUE, rvalue=NULL,
sigma = NULL, varcov = NULL, update=TRUE, leaveoneout=TRUE)
localLinhom(X, lambda, ..., rmax = NULL,
correction = "Ripley", verbose = TRUE, rvalue=NULL,
sigma = NULL, varcov = NULL, update=TRUE, leaveoneout=TRUE)
X |
A point pattern (object of class |
lambda |
Optional.
Values of the estimated intensity function.
Either a vector giving the intensity values
at the points of the pattern |
... |
Extra arguments. Ignored if |
rmax |
Optional. Maximum desired value of the argument |
correction |
String specifying the edge correction to be applied.
Options are |
verbose |
Logical flag indicating whether to print progress reports during the calculation. |
rvalue |
Optional. A single value of the distance argument
|
sigma , varcov |
Optional arguments passed to |
leaveoneout |
Logical value (passed to |
update |
Logical value indicating what to do when |
The functions localKinhom
and localLinhom
are inhomogeneous or weighted versions of the
neighbourhood density function implemented in
localK
and localL
.
Given a spatial point pattern X
, the
inhomogeneous neighbourhood density function
L_i(r)
associated with the i
th point
in X
is computed by
L_i(r) = \sqrt{\frac 1 \pi \sum_j \frac{e_{ij}}{\lambda_j}}
where the sum is over all points j \neq i
that lie
within a distance r
of the i
th point,
\lambda_j
is the estimated intensity of the
point pattern at the point j
,
and e_{ij}
is an edge correction
term (as described in Kest
).
The value of L_i(r)
can also be interpreted as one
of the summands that contributes to the global estimate of the
inhomogeneous L function (see Linhom
).
By default, the function L_i(r)
or
K_i(r)
is computed for a range of r
values
for each point i
. The results are stored as a function value
table (object of class "fv"
) with a column of the table
containing the function estimates for each point of the pattern
X
.
Alternatively, if the argument rvalue
is given, and it is a
single number, then the function will only be computed for this value
of r
, and the results will be returned as a numeric vector,
with one entry of the vector for each point of the pattern X
.
If rvalue
is given, the result is a numeric vector
of length equal to the number of points in the point pattern.
If rvalue
is absent, the result is
an object of class "fv"
, see fv.object
,
which can be plotted directly using plot.fv
.
Essentially a data frame containing columns
r |
the vector of values of the argument |
theo |
the theoretical value |
together with columns containing the values of the
neighbourhood density function for each point in the pattern.
Column i
corresponds to the i
th point.
The last two columns contain the r
and theo
values.
Mike Kuhn, \adrian and \rolf
Kinhom
,
Linhom
,
localK
,
localL
.
X <- ponderosa
# compute all the local L functions
L <- localLinhom(X)
# plot all the local L functions against r
plot(L, main="local L functions for ponderosa", legend=FALSE)
# plot only the local L function for point number 7
plot(L, iso007 ~ r)
# compute the values of L(r) for r = 12 metres
L12 <- localL(X, rvalue=12)
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