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Cyan comments on What is Bayesianism? - Less Wrong

81 Post author: Kaj_Sotala 26 February 2010 07:43AM

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Comment author: Cyan 27 February 2010 10:53:11PM *  2 points [-]

And that's never the actual case, so our arguments are never sound in this sense, because we are forced to work from prior information that isn't true.

One does generally resort to non-Bayesian model checking methods. Andrew Gelman likes to include such checks under the rubric of "Bayesian data analysis"; he calls the computing of posterior probabilities and densities "Bayesian inference", a preceding subcomponent of Bayesian data analysis. This makes for sensible statistical practice, but the underpinnings aren't strong. One might consider it an attempt to approximate the Solomonoff prior.

Comment author: wnoise 28 February 2010 07:31:41AM 0 points [-]

Yes, in practice people resort to less motivated methods that work well.

I'd really like to see some principled answer that has the same feel as Bayesianism though. As it stands, I have no problem using Bayesian methods for parameter estimation. This is natural because we really are getting pdf(parameters | data, model). But for model selection and evaluation (i.e. non-parametric Bayes) I always feel that I need an "escape hatch" to include new models that the Bayes formalism simply doesn't have any place for.

Comment author: Cyan 28 February 2010 02:56:58PM 0 points [-]

I feel the same way.