请教Bayesian regression?

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请问Bayesian regression或Bayesian method和通常的回归有什么不同呢？

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关键词：regression regressio Bayesian regress Bayes Bayesian regression

In classical econometrics, we assume that the true parameters, say, alpha and beta, are fixed. they are points.

also, to evaluate different models, we need that model A is nested in Model B.

Bayesians assume the true parameter follows a distribution. Of course, a point a just a degenerate distribution.

Bayesian model selection is free from nesting constarints.

In order to estimate a model, you must have some prior(s) for the parameter of inetrest.

A lot of numerical methods have a close link to Bayesian methods.

Sometimes, a large fraction of the effort is in the selection of priors aiming to find a analytical posterior, or partly analytical results.

.................

One needs to be very good in Matrix Algebra to do Bayesian methods

[此贴子已经被作者于2005-11-3 20:06:17编辑过]

希望大家多提供这方面的资料哦

谢谢zhaosweden的解答！

可是还是不是太明白，我就是在有关矩阵的估计中看到这种方法，但采用这种方法有什么特殊意义呢，比如有分布的alpha and beta又意味着什么呢？在什么情况下需要采用这种方法呢？

'alpha and beta'

y = a + bx + e where a = alpha  b = beta and e = error

well, in a matrix system or we call it state space model, a regression can be represented as:

y = F*X + v  

F = F_hat + w

------->

F = [a b] and X = [1 x]'

bayesian method can be applied. a and b are two time-varying parameters.

[此贴子已经被作者于2006-11-27 22:22:59编辑过]

现在bayesian用处很广,如果有比较系统的资料总结就好了