I've just switched the text of my Bayesian stats course to the second
edition of Peter Lee's book. The second edition added a chapter on
hierarchical models and also one on MCMC and EM. It is the only text
I've been able to find that is appropriate for a first course in
Bayesian stats for students with an engineering orientation. I need
a book that doesn't shrink from mathematics, but also doesn't
emphasize proofs. Engineers can do math, but they're more interested
in applications than proofs, and they need intuitive understanding of
why results are true rather than formal derivations.
Kathy Laskey
At 10:55 AM -0800 1/12/01, Stefano Monti wrote:
>
>I would recommend Gelman et al.'s "Bayesian Data Analysis" (1995) for a good
>intro (Chapters 5 (basics) and 13 (hierarchical lim's)). Best,
>
>- -- ste
>
>Gordon Hazen wrote:
>>
>> Hierarchical models are discussed in many graduate-level Bayesian
>> textbooks, for example, Bernardo & Smith (Wiley 1994), C.P. Robert
>> (Springer 1994), and Berger (Springer 1985).
>>
>> Gordon Hazen
>
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