If you start with an imprecise or "uninformative" prior, then updating with
new evidence will generate a more precise or informed posterior -- how much
more informed depends on the likelihood's ability to discriminate.
But Bayesian updating does not necessarily result in more precision -- the
prior could have been very precise and the evidence a surprise given that
prior -- this results in a less precise posterior.
Eventually (as more and more "surprising" evidence is observed), the
posterior becomes more precise as it concludes that the original priors were
incorrect.
Bob
-----Original Message-----
From: Dongsong Zeng <zengdong@pilot.msu.edu>
To: uai@CS.ORST.EDU <uai@CS.ORST.EDU>
Date: Friday, June 04, 1999 12:28 PM
Subject: BN prior prob
>Hi,
>
>if my Belief Networks starts with unprecise prior probabilities, can I get
>precise results? How and Why? Any advices are highly appreciated.
>
>Thank you very much.
>
>
> --
>Dongsong Zeng
>
>Email:zengdong@pilot.msu.edu