Hi Ralf, These are functions that generate data sets when invoked, like Numpy already does with mathematical distributions.
On Sat, Jan 18, 2020, 12:32 PM Ralf Gommers <ralf.gomm...@gmail.com> wrote: > > > 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 >> > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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