Virgilio Gomez-Rubio writes: > Diggle (2003), for example, describes what you ask and most of the > examples in the book can be reproduced using package Splancs. Check > manual page of function mse2d and references (in Splancs) as well.
I beg to disagree. The function 'Kmeasure' in spatstat does not have a counterpart in any other R package, to my knowledge. The function mse2d (splancs) is not appropriate for selecting the sigma parameter in Kmeasure. `Kmeasure' calculates an estimate of the `reduced second moment measure' of a point process. This is completely different from the first moment (`intensity') function of the point pattern, which is done by 'density.ppp' in spatstat and by 'kernel2d' in splancs. The commands density.ppp (spatstat) and kernel2d (splancs) take a point pattern, and effectively replace each point in the pattern by a copy of the kernel, then add up these kernels to get an intensity function. The command Kmeasure (spatstat) takes a point pattern, forms the list of all PAIRS of distinct points in the pattern, computes the vectors that join the first point to the second point in each pair, treats these vectors as a pattern of `points', and applies a kernel smoother to them. Kmeasure is a generalisation of Ripley's K-function. The value of K(r) is equal to the total integral of the pixel values of the Kmeasure image inside a circle of radius r centred at the origin. The main reason for looking at the second moment measure rather than just the K-function is to look for anisotropic or shape effects. If the point pattern was a regular hexagonal packing, then the Kmeasure image would reveal the hexagonal shape. `spatstat' is the only R package that provides this functionality, as far as I know. There are no well-established techniques for choosing the smoothing parameter when estimating the second moment measure. The algorithm given in mse2d (splancs) for choosing the smoothing bandwidth for kernel2d (splancs) is not designed for, and is probably not appropriate for, choosing the bandwidth for `Kmeasure'. I guess you could use it as a ballpark figure / starting value to play around with. In general terms, spatstat is by far the largest and most extensive R package for analysing spatial point patterns. The writer's recommendation to ignore this huge package is a bit misguided. Adrian Baddeley _______________________________________________ R-sig-Geo mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-geo
