prior probability is a blog inspired by Bayesian methods, computer science, and Oliver Wendell Holmes’s prediction theory of law. We also like to blog about the philosophy of probability, spontaneous order, and prediction markets. In addition, we feature our love of maps — especially unorthodox and unusual maps — as well as various odds and ends of special interest to us, including all things Cuban, Caribbean, and Latin American. (Image below courtesy of Giovanni Parmigiani.)

Hey, where did you get your priors?

12 Responses to About

  1. Hello: I finally hear from you. Love aunt Julie

  2. Mayo says:

    The “washout theorems” lead to converge in very special cases with non-extreme priors, assuming iid data, and supposing you are concerned with assessing an event where there are long-run repetitions. None of these assumptions hold in appraising scientific hypotheses. Even then it can be shown that two agents will have posteriors that differ by as much as one wants. (Kyburg). But the real problem with appealing to wash-out theorems is that this has nothing to do with our critical appraisal of scientific inferences and the data before us right now.We scrutinize how well or poorly tested claims are, and do not settle for “if you keep going on with iid long-run repetitions of the same study, you should eventually converge”. We want approximate truth, not mere coherence. Finally, the possibility of eliciting subjective priors has been deemed such a waste of time in science that it is rarely done in practice, to my knowledge. The most popular Bayesian approaches appeal to nonsubjective or “default” priors that do not influence the data too much. But even there, it’s unclear what they mean (they are not beliefs, being improper) and there are rival default prior systems that recommend very different nonsubjective priors (e.g., Berger vs Bernardo priors). You can find discussion on my blog and related publications.

    • enrique says:

      Thanks for your thoughtful comment … Also, please “stay tuned” as I’m in the process of reading chapter 3 of your excellent book on “Error and Growth of Experimental Knowledge” to better appraise your critique of Bayesian subjectivism in the domain of science …

      • Mayo says:

        Enrique: Thank you. That chapter is focused more on subjective Bayesianism in philosophy of science. Obviously, they are connected, but I think Bayesian statistics, in practice, deserves its own discussion. I think the situation regarding the foundations of Bayesian statistical practice has changed a lot in recent times: with exceptions, it seems that even those who still believe in subjective philosophical foundations, deep down, do not apply it. Or, do you think they do? That’s practically the only topic that requires updating in a new edition of EGEK (Mayo 1996). Here’s a relevant post: http://errorstatistics.com/2012/11/21/irony-and-bad-faith-deconstructing-bayesians-reblog/

    • enrique says:

      I took the liberty of reblogging your amazing slides on “The science wars and the statistics wars,” which I found very helpful. I am enjoying your blog very much, and you are rapidly becoming my favorite philosopher of statistics … I only wish I had discovered your work (and your blog) earlier!

    • Charlie says:

      Guys, I need to read up on this to understand whats going on. what are prior probabilities. what is a “prior probability,” who are Berger and Bernardo?

      • Hi Charlie. I’m embarrassed to say that I don’t know off the top of my head who Berger and Bernardo are … But I will find out.

        As for prior probabilities, I would be happy to say a word or two. Briefly, a “prior” (or “prior probability”) is a degree of belief one has that a proposition is true or false. The main thing is that our beliefs are not all or nothing (i.e. either TRUE or FALSE) but instead we have degrees of belief ranging from 0 to 1. For example, if you strongly believe it won’t rain today (but are not 100% sure that it won’t rain), you might assign this belief a value of .9 or .8, depending on how strong your belief is. Notice too that degrees of belief are subjective: I might assign a low value, while you might assign a high value.

  3. Katelyn Scafidi says:

    Hi Prof. Pujol! I am still following your blogs! I would like to catch up and see how you are and pick your brain about some topics. Let me know if you are ever free.

  4. Pingback: Was Holmes a Bayesian? | prior probability

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