local_k_cross_inhom | R Documentation |
Computes spatially-weighted versions of the local K-function or L-function, defined by Getis and Franklin (1987).
local_k_cross_inhom(X, i, j, lambdaI = NULL, lambdaJ = NULL, ..., correction = "Ripley", verbose = TRUE, rvalue = NULL, lambdaIJ = NULL, sigma = NULL, varcov = NULL)
X |
Multitype point pattern ( |
i |
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 |
j |
The type (marks value) of the points in X to which distances are
measured. A character string (or something that will be converted to a
character string'). Defaults to the second level of |
lambdaI |
Optional. Values of the estimated intensity of the sub-process
of points of type |
lambdaJ |
Optional. Values of the estimated intensity of the sub-process
of points of type |
... |
Ignored. |
correction |
String sprecifying the edge correction to be applied.
Option are |
verbose |
Logical flag indicating whether to print progress reports during the calculation. |
rvalue |
Optional. A single value of the distance argument r at which the function L or K should be computed. |
lambdaIJ |
Optional. A matrix containing estimates of the product of the
intensities |
sigma |
Optional argument passed to |
varcov |
Optional argument passed to |
The command local_l_cross_inhom
computes the neighbourhood density function,
a local version of the L-function (Besag's transformation of Ripley's
K-function) proposed by Getis and Franklin (1987), for 2 types in a multitype
spatial point pattern. The command local_k_cross
computes the corresponding
local analogue of the cross-type K-function.
Given a multitype spatial point pattern X
with types i
and j
,
the neighbourhood density function
L[ij](r) associated with the ith point
in X
is computed by
L[ij](r) = sqrt( (a/((n[j])* pi)) * sum[j] e[i,j])
where the sum is over all points j that lie
within a distance r of the ith point,
λ[j] is the estimated intensity of type j of the
point pattern at the point j, and e[i,j] is an edge correction
term (as described in Kest
).
The value of L[ij](r) can also be interpreted as one
of the summands that contributes to the global estimate of the cross-type L-
function.
By default, the function L[ij](r) or
K[ij](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 i 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 i of the pattern X
.
Computation can be done in parallel by registering a parallel backend for
the foreach
package.
If rvalue
is given, the result is a numeric vector of equal
length to the number of points in X_i.
If the codervalue 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 r at which the function K has been estimated |
theo |
the theoretical value K(r) = pi * r^2 or L(r)=r for a stationary Poisson process |
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.
Getis, A. and Franklin, J. (1987) Second-order neighbourhood analysis of mapped point patterns. Ecology 68, 473–477.
localLinhom
localKinhom
Lcross.inhom
Kcross.inhom
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