I found this a few months ago, but for the life of me I can't remember what the function or package was, and I have had no luck finding it this week.
I have found, again, the functions for working with distributions like Cauchy, F, normal, &c., and ks.test, but I have not found the functions for estimating the distribution parameters given a vector of values. What I need to do is estimate the distribution parameters for each candidate distribution, and then test to see which gives the best fit to the data. I want to examine the question, given this dataset (which may have thousands of records), does the normal or cauchy distribution fit the data best, and which what parameters. It will not be known a priori whether or not the most appropriate distribution is non-central, though we do know that often (not always) values of medium size in absolute value are more often positive than negative and that very large values are more often negative than positive. Could someone please give me a gentle reminder of the package and function(s) I ought to be examining? Thanks Ted -- View this message in context: http://www.nabble.com/library-function-that-estimates-parameters-of-well-known-distributions-from-empirical-data--tp19323700p19323700.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
