Lest(X, ...)"ppp", or data
in any format acceptable to as.ppp().
Kest
to control the estimation procedure.
"fv", see fv.object,
which can be plotted directly using plot.fv.Essentially a data frame containing columnstogether 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.
var.approx=TRUE is given, the return value
includes columns rip and ls containing approximations
to the variance of $Lest(r)$ under CSR.
These are obtained by the delta method from the variance
approximations described in Kest.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.
Kest,
pcf
data(cells)
L <- Lest(cells)
plot(L, main="L function for cells")
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