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diff --git a/gsl-1.9/randist/TODO b/gsl-1.9/randist/TODO new file mode 100644 index 0000000..4257730 --- /dev/null +++ b/gsl-1.9/randist/TODO @@ -0,0 +1,58 @@ +* add Erlang dist back in? + +* DONE, for mu. + + Note that we need to get rid of mu when it is not the mean. + + From: Brian Gough <bjg@network-theory.co.uk> + To: briggsk@info.bt.co.uk + Cc: gsl-discuss@sourceware.cygnus.com + Subject: Re: Pareto Distribution + Date: Sun, 9 Jul 2000 20:05:03 +0100 (BST) + + Yes, we should adopt the conventions from a standard reference book -- + the existing functions are drawn from a variety of sources, mostly + Devroye's book on Random Variates (which is public domain, but not + available electronically unfortunately). Maybe the three volumes of + Johnson & Kotz on Univariate Distributions would do, for + example. Patches are welcome from anyone who wants sort this out. + + Keith Briggs writes: + > Another thing to think about: some of the other distributions + > have a argument `mu' to the C function which is a parameter + > which is not the mean. This is non-standard and confusing. + > (Also, in the Pareto function, `a' is normally called beta, + > `b' is normally called alpha.) + > + > Keith + > + > +-------------------------------------------------------------------+ + > | Dr. Keith M. Briggs, Complexity Research Group, BT Research Labs. | + > | Adastral Park admin2 pp5, Martlesham Heath, IP5 3RE, Suffolk, UK | + > | Tel. 01473 641 911 Fax. 01473 647 410. Home tel: 01473 625 972 | + > | www.bt.com | personal homepage: www.labs.bt.com/people/briggsk2/ | + > +-------------------------------------------------------------------+ + + +* The exponential power distribution method could be speeded up by +using a rational function approximation for the rejection scaling +parameter. + +* Do something about the possibility of the user providing invalid +parameters (e.g. negative variance etc). Not sure what to do though, +since returning an error code is not possible. Maybe just return zero. + We should return NAN in this case, and for the CDFs. + +* Add the triangular distribution. + +* Look at Marsaglia & Tsang, "The Monte Python Method for generating +random variables", ACM TOMS Vol 24, No 3, p341 + +and the paper on the Ziggurat Method: Journal of Statistical Software, +Volume 05 Issue 08. George Marsaglia and Wai Wan Tsang. "The ziggurat +method for generating random variables" + +* Should 0 be included in distributions such as the exponential +distribution? If we want a consistent behaviour, is it included in +others? Note that 1-gsl_rng_uniform() can have a slight loss of +precision when the random float is small. |