x tcdf y is the CDF at y of the t-distribution with x degrees of freedom tcdf=: 4 : 0 assert. y<%:x 0.5 + y * (!-:x-1) * ((0.5,-:1+x) H. 1.5 x%~-*:y) % (%:o.x) * !<:-:x )
5 tcdf 2.01505 1.47588 0.95 0.899999 The y<%:x restriction is rather limiting. Perhaps Ewart Shaw or others knowledgeable on this subject know of a better formulation for the CDF. ----- Original Message ----- From: Brian Schott <[EMAIL PROTECTED]> Date: Tuesday, August 12, 2008 6:43 Subject: Re: [Jprogramming] general Gamma distribution To: Programming forum <[email protected]> > Robert, > > I may have misunderstood your original question > regarding the student's T distribution. I thought you were > asking for a way to generate random variates from the T, but > you may have been asking for a way to compute probabilities > from the student's T. If the latter was your question, I am > afraid that computing probabilities is much more difficult > and I have no thoughts about that. > > OTOH if you are thinking about constructing > confidence intervals around sample means using the student > T, then you need random normal variates and a table lookup > of a student's T to build the interval(s) and it would be > easier to read in a table of student's T values or just the > ones you need for the sample sizes and levels of confidence > you are simulating. > > > On Tue, 12 Aug 2008, Robert Cyr wrote: > > + Bran Schott said: > + T_k = Z/sqrt(U/k) > + > + I have seen the usual formulas for building the distribution > function,but+ none like this one. It seems very interesting. > + > + As for the cdf required for the usual confidence > interval, accuracy comes > + at a price. Perhaps less accurate but useful is a simple > list of a few > + dozen factors and a simple formula. > + > + Robert Cyr ---------------------------------------------------------------------- For information about J forums see http://www.jsoftware.com/forums.htm
