actually, I had it right all along. that is, m<- runif(); s<- runif(); df<-runif()*10+1 # get some parameters...any parameters x <- rt( 100000, df )*s + m # create random draws library(MASS) fitdistr(x, "t") # confirm properties
will work. (josh suggested working with the skewness parameter, ncp, which solves a different problem.) I believe that I was confused, because fitdistr will not necessarily assign the sample mean to be its maximum-likelihood estimate of the population mean. /iaw ______________________________________________ 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.
