wuzzy wrote:
> [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.

Ah, have you forgotten to use a link function?  Logistic regression uses 
a logit link function to go between the linear predictor (which variate 
between + and - infinity) and the probability (which varies between 0 
and 1).  Or, in practice:

If eta ~  N(mu, sigma)
then p = exp(eta)/(1+exp(eta))

If sigma is too large, then the prior for p is U-shaped.

Bob

-- 
Bob O'Hara

Rolf Nevanlinna Institute
P.O. Box 4 (Yliopistonkatu 5)
FIN-00014 University of Helsinki
Finland
Telephone: +358-9-191 23743
Mobile: +358 50 599 0540
Fax:  +358-9-191 22 779
WWW:  http://www.RNI.Helsinki.FI/~boh/

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