LOST CAUSES IN STATISTICS II: Noninformative Priors

Just a link today, to a nice post I came across (from mid last year) on the blog of Larry Wasserman, who if you are not familiar with him is a professor in the Department of Statistics and also the Machine Learning Department at Carnegie Mellon University. He is rather well know in the statistics community.

Here he criticises somewhat harshly the whole project of looking for non-informative priors. As much as I, like many, feel the compulsion to wish for such things, I am inclined to agree with Larry that they simply don’t exist. Yet, as he also discusses, some of the formal constructions in this direction can still be useful in the right situation.

LOST CAUSES IN STATISTICS II: Noninformative Priors.

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