Posts Tagged With: Dutch books

Does the Bayesian Diet Call For Error-Statistical Supplements?

Some of the recent comments to my May 20 post leads me to point us back to my earlier (April 15) post  on dynamic dutch books, and continue where Howson left off:

“And where does this conclusion leave the Bayesian theory? ….I claim that nothing valuable is lost by abandoning updating rules.  The idea that the only updating policy sanctioned by the Bayesian theory is updating by conditionalization was untenable even on its own terms, since the learning of each conditioning proposition could not  itself have been by conditionalization.” (Howson 1997, 289).

So a Bayesian account requires a distinct account of empirical learning in order to learn “of each conditioning proposition” (propositions which may be statistical hypotheses).  This was my argument in EGEK (1996, 87)*. And this other account, I would go on to suggest, should ensure the claims (which I prefer to “propositions”) are reliably warranted or severely corroborated.

*Error and the Growth of Experimental Knowledge (Mayo 1996):  Scroll down to chapter 3.

Categories: Statistics | Tags: , ,

Betting, Bookies and Bayes: Does it Not Matter?

On Gelman’s blog today he offers a simple rejection of Dutch Book arguments for Bayesian inference:

“I have never found this argument appealing, because a bet is a game not a decision. A bet requires 2 players, and one player has to offer the bets.”

But what about dynamic Bayesian Dutch book arguments which are thought to be the basis for advocating updating by Bayes’s theorem?  Betting scenarios, even if hypothetical, are often offered as the basis for making Bayesian measurements operational, and for claiming Bayes’s rule is a warranted representation of updating “uncertainty”. The question I had asked in an earlier (April 15) post (and then placed on hold) is: Does it not matter that Bayesians increasingly seem to debunk  betting representations?

Categories: Statistics | Tags: ,

U-Phil: Jon Williamson: Deconstructing Dynamic Dutch Books

Jon Williamson

I am  posting Jon Williamson’s* (Philosophy, Kent) U-Phil from 4-15-12

In this paper (Synthese 178:67–85) I identify four ways in which Bayesian conditionalisation can fail. Of course not all Bayesians advocate conditionalisation as a universal rule, and I argue that objective Bayesianism as based on the maximum entropy principle should be preferred to subjective Bayesianism as based on conditionalisation, where the two disagree.

Conditionalisation is just one possible way of updating probabilities and I think it’s interesting to see how different formal approaches compare.

*Williamson participated in our June 2010 “Phil-Stat Meets Phil Sci” conference at the LSE, and we jointly ran a conference at Kent in June 2009.

Categories: Statistics, U-Phil | Tags: , , , ,

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