I am having a data set that causes flexmix::KLdiv to produce NA as a result and I was told that increasing the sensitivity of the 'esp' value can be used to avoid a lot of values being set to a default (which presumably causes the problem).
Now here my question. When running KLdiv on a normal distribution: a <- rnorm(50000) b <- rnorm(50000) mydata <- cbind(a,b) KLdiv(mydata, esp=1e-4) KLdiv(mydata, esp=1e-5) KLdiv(mydata, esp=1e-6) KLdiv(mydata, esp=1e-7) KLdiv(mydata, esp=1e-8) KLdiv(mydata, esp=1e-9) KLdiv(mydata, esp=1e-10) KLdiv(mydata, esp=1e-100) the result is stable independent from the chosen esp accuracy. However, when I run the data on a distribution such as values in a given range, I get NA and the method seems not to work independently of how high I choose the accuracy. y1 <- sample(1:1280, 200000, replace=T) y2 <- sample(1:1280, 200000, replace=T) mydata2 <- cbind(y1,y2) KLdiv(mydata2, esp=1e-4) KLdiv(mydata2, esp=1e-5) KLdiv(mydata2, esp=1e-6) KLdiv(mydata2, esp=1e-7) KLdiv(mydata2, esp=1e-8) KLdiv(mydata2, esp=1e-9) KLdiv(mydata2, esp=1e-10) KLdiv(mydata2, esp=1e-100) Am I doing something wrong here? Does KL have any distributional assumptions that I violate? Best, Ralf ______________________________________________ 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.
