The R code below produces (after running for a few minutes on a decent computer) the plot shown at the following location:
http://n2.nabble.com/Is-there-a-physical-and-quantitative-explanation-for-this-plot--td2542321.html I'm just taking the mean of a given set of random variables, where the set size is increased. There appears to be a quick convergence and then a pretty steady variance out to a set size of 10,0000. I'm just wondering if there is a statistical explanation out there for this convergence and it has been explored further. Thanks again. # First case N<-100000 X<-rnorm(N) step_size<-1 # Groups g<-rep(1:(N/step_size),each=step_size) # The result tmp_output<-tapply(X[1:length(g)],g,mean) length_tmp_output<-length(tmp_output) tmp_x_vals<-rep(step_size,length_tmp_output) plot(tmp_x_vals, tmp_output, xlim=c(0,10000)) #points(tmp_x_vals, tmp_output) for(ii in 1:10000) { step_size<-ii # Groups g<-rep(1:(N/step_size),each=step_size) # The result #tmp_output<-tapply(X,g,mean) tmp_output<-tapply(X[1:length(g)],g,mean) length_tmp_output<-length(tmp_output) tmp_x_vals<-rep(step_size,length_tmp_output) points(tmp_x_vals, tmp_output) } ______________________________________________ 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.
