On Fri, Jan 17, 2020 at 3:46 AM Michael Lance <michael.la...@gmail.com> wrote:
> TLDR; > I think this could be a useful contribution to NumPy, but I want to get > feedback on where it should go (either in NumPy or elsewhere). > I have functions using numpy.random which invoke the 8 "Real" data sets as > estimated by Ted Micceri in 1989. These can be useful in Monte Carlo > simulations. > Thanks for the suggestion Michael. This seems too specialized for NumPy. Also, it's not 100% clear whether you want to add functions or data sets; NumPy doesn't want to ship any data sets. It sounds to me like these would be best in their own package. Cheers, Ralf > Background info: > > Parametric inferential statistics generally assume normal distributions > (though kurtosis presents less of an issue than skew). However, in > "nature", distributions are often not normal. In 1989, Ted Micceri's study ( > http://psycnet.apa.org/record/1989-14214-001) on real data sets resulted > in the estimation of 8 "Real" distributions. Using these distributions in > simulations help to produce more realistic types I and II error rate and > power estimates, particularly for smaller samples. > A similar module is currently available in Fortran called realpops. > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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