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Jun 11, 2020 at 14:32 history edited CommunityBot
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S Nov 20, 2017 at 7:20 history bounty ended user56834
S Nov 20, 2017 at 7:20 history notice removed user56834
Nov 19, 2017 at 15:28 answer added user36160 timeline score: 1
Nov 19, 2017 at 15:28 comment added Jeremias K @Programmer2134 I would if I felt comfortable enough with the material, but I don't. I know that what they do is deriving a Bayesian counterpart of a CLT, with certain 'posterior concentration rates' that tell you how fast the parameter posterior concentrates on a point in your parameter space as you increase the sample size, and then you basically end up finding frequentist-type consistency guarantees for your Bayesian estimators.
Nov 19, 2017 at 7:40 comment added user56834 @JeremiasK, maybe you can explain something about that in an answer?
Nov 17, 2017 at 11:45 comment added Jeremias K It is not a simple question to answer in the generality you pose it, but it is currently a really hot research topic, see for instance Judith Rousseau's work in this area: ceremade.dauphine.fr/~rousseau/publi.html
Nov 16, 2017 at 19:10 history edited Patrick CC BY-SA 3.0
Inserted clarification and example
Nov 16, 2017 at 10:36 answer added Xi'an timeline score: 10
Nov 16, 2017 at 10:21 history edited Xi'an CC BY-SA 3.0
edited tags; edited title
Nov 13, 2017 at 7:07 history tweeted twitter.com/StackStats/status/929968856889790464
S Nov 13, 2017 at 5:10 history bounty started user56834
S Nov 13, 2017 at 5:10 history notice added user56834 Canonical answer required
Nov 13, 2017 at 5:04 comment added user56834 I assume that you want the answer to assume a flat prior? Otherwise of course there is no way that the estimates could be reasonable expected to be the same in interesting general cases.
Nov 13, 2017 at 5:03 answer added user56834 timeline score: 4
Apr 25, 2013 at 19:26 answer added Stefan Wager timeline score: 3
Apr 25, 2013 at 18:00 history asked Patrick CC BY-SA 3.0