Calculates an estimate of the \(L\)-function (Besag's transformation of Ripley's \(K\)-function) for a spatial point pattern.
Lest(X, ..., correction)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 \(L\) has been estimated
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.
This command computes an estimate of the \(L\)-function
for the spatial point pattern X.
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 transformation to \(L\) was
proposed by Besag (1977).
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 \(L(r)\) is more appropriate for use in simulation envelopes and hypothesis tests.
See Kest for the list of arguments.
Besag, J. (1977) Discussion of Dr Ripley's paper. Journal of the Royal Statistical Society, Series B, 39, 193--195.
Kest,
pcf
L <- Lest(cells)
plot(L, main="L function for cells")
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