There isn’t a single piece of mathematics in either of the two papers, which leads me to expect little of them. The book (of which I’ve only seen a few pages on Amazon) does contain a chapter on Bayesian reasoning, arguing that it and IBE are “broadly compatible”. This appears to come down to the usual small-world/large-world issue: Bayes is sound mathematics (say the small-worlders) when you already have a hypothesis that gives you an explicit prior, but it must yield to something else when it comes to finding and judging hypotheses.
That something else always seems to come down to magic. It may be called IBE, or model validation, or human judgement, but however many words are expended, no method of doing it is found. It’s the élan vital of statistics.
ETA: I found the book in my university library, but only the first edition of 1991, which is two chapters shorter and doesn’t include the Bayes chapter (or any other mathematics). In the introduction (which is readable on Amazon) he remarks that IBE has been “more a slogan than an articulated philosophical theory”, and that by describing inference in terms of explanation, it explains the obscure by the obscure. From a brief scan I was not sufficiently convinced that he fixes these problems to check the book out.
Thanks for the comment. The lack of math is a problem, and I think you’ve said it nicely:
That something else always seems to come down to magic. It may be called IBE, or model validation, or human judgement, but however many words are expended, no method of doing it is found. It’s the élan vital of statistics.
Reading this book, Agnostic Inquirer, is quite the headache. It’s so obscure and filled with mights, maybes, possibly’s, and such that I constantly have this gut feeling that I’m being led into a mental trap but am not always sure which clauses are doing it. Same for IBE. It sounds common-sensically appealing. “Hey, Bayes is awesome, but tell me how you expect to use it on something like this topic? You can’t? Well of course you can’t, so here’s how we use IBE to do so.”
But the heuristic strikes me as simply an approximation of what Bayes would do anyway, so I was quite confused as to what they were trying to get at (other than perhaps have their way with the reader).
I googled “Inference to the Best Explanation”, and this paper of Gilbert Harman appears to be where the phrase was first coined, although the general idea goes back further. More recently, there’s a whole book on the subject, and lukeprog’s web site has an introductory article by the author of that book.
There isn’t a single piece of mathematics in either of the two papers, which leads me to expect little of them. The book (of which I’ve only seen a few pages on Amazon) does contain a chapter on Bayesian reasoning, arguing that it and IBE are “broadly compatible”. This appears to come down to the usual small-world/large-world issue: Bayes is sound mathematics (say the small-worlders) when you already have a hypothesis that gives you an explicit prior, but it must yield to something else when it comes to finding and judging hypotheses.
That something else always seems to come down to magic. It may be called IBE, or model validation, or human judgement, but however many words are expended, no method of doing it is found. It’s the élan vital of statistics.
ETA: I found the book in my university library, but only the first edition of 1991, which is two chapters shorter and doesn’t include the Bayes chapter (or any other mathematics). In the introduction (which is readable on Amazon) he remarks that IBE has been “more a slogan than an articulated philosophical theory”, and that by describing inference in terms of explanation, it explains the obscure by the obscure. From a brief scan I was not sufficiently convinced that he fixes these problems to check the book out.
Thanks for the comment. The lack of math is a problem, and I think you’ve said it nicely:
Reading this book, Agnostic Inquirer, is quite the headache. It’s so obscure and filled with mights, maybes, possibly’s, and such that I constantly have this gut feeling that I’m being led into a mental trap but am not always sure which clauses are doing it. Same for IBE. It sounds common-sensically appealing. “Hey, Bayes is awesome, but tell me how you expect to use it on something like this topic? You can’t? Well of course you can’t, so here’s how we use IBE to do so.”
But the heuristic strikes me as simply an approximation of what Bayes would do anyway, so I was quite confused as to what they were trying to get at (other than perhaps have their way with the reader).