> First candidates are: >>> * Non-uniform deviates (i.e. the samplers now defined in >>> Commons Math's "o.a.c.math4.distribution" package), >>> >> >> I agree this doesn't belong to commons-rng, but I'm not convinced it >> would fit a commons-rng-tools component. Maybe a component more targeted >> toward statistic algorithms? >> > > Sampling and statistics do not necessarily belong together. > [This was a discussion in CM.] > > +1
Having used commons-math to generate random deviates, the commons-math approach of coupling random deviate generation to the distributions themselves proved to be a bad development experience as well as not the most performant in the form of object instantiations. Specialized random variate generators would be a lot better design IMO.
