Lest
L-function
Calculates an estimate of Ripley's L-function for a spatial point pattern.
- Keywords
- spatial, nonparametric
Usage
Lest(...)Arguments
- ...
- Arguments passed to
Kestto estimate the K-function.
Details
This command computes an estimate of the L-function for a spatial point pattern. The L-function is a transformation of Ripley's K-function, $$L(r) = \sqrt{\frac{K(r)}{\pi}}$$ where $K(r)$ is the K-function.
See Kest for information
about Ripley's K-function.
The command Lest first calls
Kest to compute the estimate of the K-function,
and then applies the square root transformation.
For a completely random (uniform Poisson) point pattern, the theoretical value of the L-function is $L(r) = r$. The square root also has the effect of stabilising the variance of the estimator, so that L is more appropriate for use in simulation envelopes and hypothesis tests.
Value
- An object of class
"fv", seefv.object, which can be plotted directly usingplot.fv.Essentially a data frame containing columns
r the vector of values of the argument $r$ at which the function $L$ has been estimated theo the theoretical value $L(r) = r$ for a stationary Poisson process - together with columns named
"border","bord.modif","iso"and/or"trans", according to the selected edge corrections. These columns contain estimates of the function $L(r)$ obtained by the edge corrections named.
See Also
Examples
data(cells)
L <- Lest(cells)
plot(L, main="L function for cells")