The ML estimate of lambda is the mean, so no need for (iterative) optimization. See eg: http://mathworld.wolfram.com/MaximumLikelihood.html hth, Ingmar
On Fri, Feb 11, 2011 at 8:52 AM, Antje Niederlein <[email protected] > wrote: > Hello, > > I tried to fit a poisson distribution but looking at the function > fitdistr() it does not optimize lambda but simply estimates the mean > of the data and returns it as lambda. I'm a bit confused because I was > expecting an optimization of this parameter to gain a good fit... > If I would use mle() of stats4 package or mle2() of bbmle package, I > would have to write the function by myself which should be optimized. > But what shall I return? > > -sum((y_observed - y_fitted)^2) > > ? > > Any other suggestions or comments on my solution? > > Antje > > ______________________________________________ > [email protected] 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. > [[alternative HTML version deleted]] ______________________________________________ [email protected] 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.
