You posted this earlier. Do not repost, please. It was seen. -- Bert
On Mon, Mar 18, 2013 at 3:28 PM, To . . <kid...@hotmail.com> wrote: > > Hello > > I am trying to find an automated way of fitting a mixture of normal and > log-normal distributions to data which is clearly bimodal. > Here's a simulated example: > x.1<-rnorm(6000, 2.4, 0.6) > x.2<-rlnorm(10000, 1.3,0.1) > X<-c(x.1, x.2) > hist(X,100,freq=FALSE, ylim=c(0,1.5))lines(density(x.1), lty=2, lwd=2) > lines(density(x.2), lty=2, lwd=2) > lines(density(X), lty=4) > > Currently i am using mixtools and just run: > library(mixtools) > mixmdl = normalmixEM(X, k=2, epsilon = 1e-08, maxit = 1000, > maxrestarts=20, verb = TRUE, fast=FALSE, ECM = FALSE, arbmean = TRUE, > arbvar = TRUE) > plot(mixmdl,which=2)lines(density(X), lty=2, lwd=2) > > This is obviously not the best way of doing this. > The estimates it gives are: > mu 3.6595737(x.2 log()=1.29) 2.3113135(x.1) > > These are not too far off but I was wondering if someone knows of a better > R package/way of doing this or has any hints that would help me coding it > from scratch (EM+writing down the formulae for ML? but... would this really > be better than using a > "more-advanced-already-available-package-made-by-pros"?). > The objective is to estimate threshold values at specific FDRs. (some help > with that would also be most helpful.) > > Thanks to all in advance! > To' > ______________________________________________ > 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. > -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm [[alternative HTML version deleted]] ______________________________________________ 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.
