Lest(...)Kest
    to estimate the $K$-function."fv", see fv.object,
  which can be plotted directly using plot.fv.Essentially a data frame containing columns
"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 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 $K$ is more appropriate for use in simulation envelopes and hypothesis tests.
Kest,
  pcfdata(cells)
 L <- Lest(cells)
 plot(L, main="L function for cells")Run the code above in your browser using DataLab