[EMAIL PROTECTED] (Herman Rubin) wrote in message news:<[EMAIL PROTECTED]>... > In article <[EMAIL PROTECTED]>, > Duncan Smith <[EMAIL PROTECTED]> wrote: > > >"wuzzy" <[EMAIL PROTECTED]> wrote in message > >news:[EMAIL PROTECTED] > >> I asked this elswhere, this group may be more appropriate, appologies > >> for simple question? > > >> Can someone describe an algorithm in MS Excel to find the posterior > >> distribution given a likelihood function (=BINOMDIST) and a prior > >> distribution (=NORMDIST mu=0, sigma=0.05)? > >> I know that it is proportional to L*P (likelihood times prior). > >> [anyone know how to calculate the denominator in excel?] > > >> But what is an exact algorithm?! > > >> For instance I was considering sampling 10 random parameters in ten > >> columns > >> of BINOMDIST()*NORMDIST(from 1..10) for each case. But what does this > >> product tell me? how do I actually plot the distribution? > > >> Thanks > > >Does it make sense to have a Normal prior (particularly with mu=0) with a > >Binomial likelihood? If a Beta prior makes at least as much sense it makes > >the maths much easier. > > >Duncan
True, I do expect to see alot of #DIV/0 with mu=0. I've posted something like what I was looking for on http://members.rogers.com/spsstutor/bayes.xls (not sure if the site is up properly though) What I was trying to do (probably failed) is a bayesian logistic regression. I like having the likelihood and prior on separate sheets each sampling parameters from -0.07 to +0.07. Then I multiply these and divide by the SUMPRODUCT(likelihood,prior) to get the posterior and I use a new sheet to draw it out. My sheet may be totally wrong but that is the idea of what I was looking for.. Also wanted to experiment with the effect of changing the sample size and changing the sigma, mu of the prior on the posterior I can do it with the above, but not sure if its right (just experimenting). . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
