Recently, I have been working with some data that look like two overlapping gaussian distributions. I would like to either
1) determine the mean and SD for each of the two distributions OR 2) get some (bayesian ?) statistic that estimates how likely an observation is to belong to the left-hand or right-hand distribution In case I'm using the wrong language, my data looks something like this: B <- rnorm(500,40,10) H <- rnorm(500,80,5 ) N <- runif(200,0,99) D <- c(B,H,N) Where B=background, H=hits, N=noise, and D=my observed distribution I have seen analyses like this in the past, but I can't remember what it is called. If somebody out there can point me towards an R function, or even the cannonical name for this kind of model, I think I can write the necessary code. Thanks in advance, Mark ______________________________________________ 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.
