On Fri, Dec 24, 2010 at 10:13 AM, Pavel Ryzhov <pavel.ryz...@gmail.com>wrote:
> Hi, > > I've implemented a Stable random generator based on Chambers-Mallows-Stuck > method as it is described in "Handbook of computational statistics: concepts > and methods" by James E. Gentle, Wolfgang Härdle, Yuichi Mori > Thanks! Looks good after quick review. > > But I'm stuck on unit-testing of the generator as I don't have estimators > of stable distribution parameters. I cannot use moments to > approve/disapprove if the sample satisfies to the distribution > > Thus I've to fall back to tests with known moments: > 1. Normal distribution (alpha = 2 and beta=0.0) > 2. Cauchy distribution (alpha = 1 and beta=0.0) > 3. Alpha > 1 > The alpha interval (0, 1) stays untested. > > The questions are: > 1. Is it worth to include it into Commons Math? > Yes. > 2. Are these unit-tests enough for acceptance? > What I try to do in these cases is find another implementation to compare against of reference data somewhere. I have not checked yet, but most likely R has this distribution. The reference data for most of the other distribution comes from R. Obviously, these tests are not definitive; but agreement with R is a good indication that the implementation is correct. Have a look in src/test/R. See, for example, TDistributionTestCases.R. Phil > > Pavel > --------------------------------------------------------------------- > To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org > For additional commands, e-mail: dev-h...@commons.apache.org > >
