Dear R-Experts, I was wondering how to fit a cumulative gaussian to a set of empirical data using R. On the R website as well as in the mail archives, I found a lot of help on how to fit a normal density function to empirical data, but unfortunately no advice on how to obtain reasonable estimates of m and sd for a gaussian ogive function. Specifically, I have data from a psychometric function relating the frequency a subject's binary response (stimulus present / absent) to the strength of a physical stimulus. Such data is often modeled using a cumulative gaussian function. I have tried to implement such a fitting algorithm in R, but unfortunately, I was not successful. Maybe anyone on the list already coded a script for such purposes or could help me otherwise???
Thanks in advance, Matthias ______________________________________________ R-help@stat.math.ethz.ch 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.
