Calculates an estimate of the multitype L-function
(from type i
to any type)
for a multitype point pattern.
Ldot(X, i, ..., from)
The observed point pattern, from which an estimate of the dot-type \(L\) function \(L_{ij}(r)\) will be computed. It must be a multitype point pattern (a marked point pattern whose marks are a factor). See under Details.
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)
.
Arguments passed to Kdot
.
An alternative way to specify i
.
An object of class "fv"
, see fv.object
,
which can be plotted directly using plot.fv
.
Essentially a data frame containing columns
the vector of values of the argument \(r\) at which the function \(L_{i\bullet}\) has been estimated
the theoretical value \(L_{i\bullet}(r) = r\) for a stationary Poisson process
This command computes
$$L_{i\bullet}(r) = \sqrt{\frac{K_{i\bullet}(r)}{\pi}}$$
where \(K_{i\bullet}(r)\) is the multitype \(K\)-function
from points of type i
to points of any type.
See Kdot
for information
about \(K_{i\bullet}(r)\).
The command Ldot
first calls
Kdot
to compute the estimate of the i
-to-any
\(K\)-function, and then applies the square root transformation.
For a marked Poisson point process, the theoretical value of the L-function is \(L_{i\bullet}(r) = r\). The square root also has the effect of stabilising the variance of the estimator, so that \(L_{i\bullet}\) is more appropriate for use in simulation envelopes and hypothesis tests.
# NOT RUN {
data(amacrine)
L <- Ldot(amacrine, "off")
plot(L)
# }
Run the code above in your browser using DataLab