I normally use the following code to create a figure displaying the mark correlation function for the point pattern process "A":
M<-markcorr(A) plot(M) I have now started to use the following code to perform 1000 Monte Carlo simulations of Complete Spatial Randomness (CSR). It is a Monte Carlo test based on envelopes of the Mark correlation function obtained from simulated point patterns, normally used for Ripley's K: ME<-envelope(A, markcorr, nsim = 1000) And I produce the figure below. My question is: Is this a justified use of nsim if the envelope is based on simulations of CSR? Or should I display the Mark correlation function without the envelopes? <http://r.789695.n4.nabble.com/file/n4650579/MARKCORR_FOR_R_FORUM.png> Thanks, Tom -- View this message in context: http://r.789695.n4.nabble.com/Spatstat-Mark-correlation-function-tp4650579.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
