+1

]]>+1

]]>“and other exercises that give the model an opportunity to fail.

… I’m hoping that Bayesian modelers will be sooner to recognize their dead ends, and in my own research I’ve put a lot of effort into developing methods for checking model fit and evaluating predictions.”

That seems like a really important principle, and if Bayesian approaches are better at evaluating and giving models and theories a chance to fail, so much the better. ]]>

What on earth does that mean?

]]>Tom: If you have not already, might wish to have a look at http://www.stat.columbia.edu/~gelman/research/unpublished/objectivityr3.pdf

]]>Feynman Lectures on Physics, Vol. I section 6-3 , p 6-7

It is probably better to realize that the probability concept is in a sense subjective, that it is always based on uncertain knowledge, and that its quantitative evaluation is subject to change as we obtain more information.

]]>Rather than “subjective”, I would say that selecting a prior amounts to making a further assumption about the data model. That would be subject to a similar degree of scrutiny as any other assumption in the whole data analysis process.

]]>People don’t realize that Bayesian methods attempt to render into rigorous form the way we live. Huge challenge.

]]>D’oh!

]]>“Thomas Bayes, a 17th-century English cleric”

Make that 18th century English cleric. The KDnuggets article also has that typo.

]]>