Dear All, I would like to estimate let say  95th percentile of  the distribution of \tau=max|\hat L(r)-r| for r<=r0.
using Monte Carlo simulation (the number of simulation is 20000) for a Binomial point pattern with n point in a unit square, for different n, let say n=10,20,25,30,40,50,100,200,300 and known value of r0. To proceed we estimate the Ripley K-function using R package âspatstatâ . I need please some technical comments, describing me the  âTruthâ of  the following statements about using spatstat function âKestâ. âNote that empirical K function is a step function and hence the max occurs only at a jump point. The default output of the spatstat package reports the estimated K at regular intervals and hence the max at these regular points is close to but not exactly the real max we have in mind. The importance of using the exact real max is to make sure that everyone will get the same value. If we use a sequence of regular lattice points, the value depends on the lattice size. Note also if you use the same regular points to find the max for different n, then the larger the value n, the poor the accuracy of the max approximated by the max at the regular points.â Many thanks in advance Hamid [[alternative HTML version deleted]]
_______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo