Syll borrows the title for the blog post from a 2008 article by Andrew Gelman and proceeds to quote very strong criticisms to Bayesian inference. The thing is, these are NOT Gelman's criticisms, but rather those of a hypothetical anti-Bayesian created by him to voice the objections. There are several passages in the article where this is clearly explained by Gelman, but all passages were purposefully omitted by Syll. Someone reading the blog post and not the article would rightly assume that these are criticisms that Gelman is raising himself (much like the April fool's joke on which the article is based). Worse, Syll does not make any reference whatsoever to the follow up article where Gelman presents a spirited defence of Bayesian methods.

Syll says that his purpose was to quote from an eminent statistician (Andrew Gelman) who "realized that these are strong arguments [against Bayesianism] to be taken seriously—and ultimately accepted in some settings and refuted in others." That is fine, but why do so in a way that implies that said statistician is trying to attack Bayesian inference, when in fact he is defending it?

Finally, in response to my comment Syll says: "A quote is — yes — a quote. Nothing more, nothing less." Oh yeah? Well start with this quote:

and compare it with:“Here follows the list of objections from a hypothetical or paradigmatic non-Bayesian:Bayesian inference is a coherent mathematical theory but I don’t trust it in scientific applications.” Andrew Gelman

Same thing right? I don't think so.“Bayesian inference is a coherent mathematical theory but I don’t trust it in scientific applications.” Andrew Gelman

Gelman is laying out the criticisms he thinks are worth dealing with by real Bayesians. You want to deal with them, Grasselli?

ReplyDeleteI don't have to deal with them, Illusionist, because Gelman himself dealt with the criticism in the rejoinder article that I quote above.

ReplyDeleteHow hard to understand is that?

"The resolution of this criticism is that Bayesian inference (and also utility theory)

ReplyDeleteare ideals or aspirations as much as they are descriptions."

"I'll retreat to the usual Bayesian answer that our default methods perform as well or better than classical default methods."

"if information is available to distinguish the groups, then it can and should be added to the model"

Gelman seems reasonable and moderate to me. If only all Bayesians were so moderate. We could then ask, Is QF the kind of field for which Gelman regards a simplistic Bayesian approach as reasonable? Or in Savage's terms, is QF about small or large worlds?