Linhom {spatstat}R Documentation

L-function

Description

Calculates an estimate of the inhomogeneous version of the L-function (Besag's transformation of Ripley's K-function) for a spatial point pattern.

Usage

  Linhom(...)

Arguments

...

Arguments passed to Kinhom to estimate the inhomogeneous K-function.

Details

This command computes an estimate of the inhomogeneous version of the L-function for a spatial point pattern

The original L-function is a transformation (proposed by Besag) of Ripley's K-function,

L(r) = sqrt(K(r)/pi)

where K(r) is the Ripley K-function of a spatially homogeneous point pattern, estimated by Kest.

The inhomogeneous L-function is the corresponding transformation of the inhomogeneous K-function, estimated by Kinhom. It is appropriate when the point pattern clearly does not have a homogeneous intensity of points. It was proposed by Baddeley, Moller and Waagepetersen (2000).

The command Linhom first calls Kinhom to compute the estimate of the inhomogeneous K-function, and then applies the square root transformation.

For a Poisson point pattern (homogeneous or inhomogeneous), the theoretical value of the inhomogeneous 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", 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 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.

Author(s)

Adrian Baddeley Adrian.Baddeley@csiro.au http://www.maths.uwa.edu.au/~adrian/ and Rolf Turner r.turner@auckland.ac.nz

References

Baddeley, A., Moller, J. and Waagepetersen, R. (2000) Non- and semiparametric estimation of interaction in inhomogeneous point patterns. Statistica Neerlandica 54, 329–350.

See Also

Kest, Lest, Kinhom, pcf

Examples

 data(japanesepines)
 X <- japanesepines
 L <- Linhom(X, sigma=0.1)
 plot(L, main="Inhomogeneous L function for Japanese Pines")

[Package spatstat version 1.25-3 Index]