# Lest

0th

Percentile

##### L-function

Calculates an estimate of Ripley's L-function for a spatial point pattern.

Keywords
spatial, nonparametric
##### Usage
Lest(...)
##### Arguments
...
Arguments passed to Kest to 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", see fv.object, which can be plotted directly using plot.fv.

Essentially a data frame containing columns

• rthe vector of values of the argument $r$ at which the function $L$ has been estimated
• theothe 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.

Kest, pcf

• Lest
##### Examples
data(cells)
L <- Lest(cells)
plot(L, main="L function for cells")
Documentation reproduced from package spatstat, version 1.18-1, License: GPL (>= 2)

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