Dear Abrams,
I will first reassure you: this list is intended for discussions of all kinds around IP, so formal questions are more than welcomed. It is just that we did not have some for a while now.
As for publishing it on stakexchange forums, it is true that the community is small, but I think the best way to go is to post your question on this list, and also to signal to people that you have posted it in a stackexchange forum that seems the most suited to you, so that people from here as well as roaming these forums can answer. This would also help increase imprecise probability visibility on those forums.
What is the most appropriate forum then depends on the question: a question on learning and Bayes update rule would most likely be adapted to st, a question about the mathematics of lower previsions to mathematics, and a question about credal network complexity to computer science. So math, cs and st, depending on your question. I guess your question could go to math. or st.
I will let the experts on Markov Chains extensions reply precisely to your technical question.
Best
Sebastien
2017-04-06 18:46 GMT+02:00 Abrams, Marshall <mabrams(a)uab.edu>:
Most of the notices that appear on this list are announcements, so it doesn’t seem appropriate to ask detailed, non-expert questions here. I hope you don’t mind if I ask a more meta-level question.
Is there an appropriate place for asking mathematical IP questions? Another mailing list?
An option that I’ve explored in the past is to ask questions about imprecise probability on mathematics the question-and-answer site math.stackexchange.com, but so far this doesn’t seem to be a site in which people knowledgeable about IP participate. (Questions on math.stackexchange are classified by “tags”. There is so little interest in IP that I’ve found no tags representing any aspect of it.) stats.stackexchange.com is another option, but that’s focused on statistics, and not all IP questions are statistics-related. mathoverflow.net is part of the same family of sites, but it’s "a question and answer site for professional mathematicians.” (Whatever that term means, it would not apply to me.)
Thanks very much-
Marshall
[In case it’s helpful, to illustrate the level of question I want to be able ask, here is the question with which I’m currently struggling: I’m reading Hermans and Skulj’s “Stochastic processes” chapter of of Introduction to Imprecise Probabilities, and I’m puzzled by the novel (to me) definition of “transition operator” in 11.3. I understand that it’s intended as a sort of generalization of the standard Markov process transition operator concept, but there’s something I’m just not seeing due to lack of experience, lack of insight, etc.: As I understand definition 11.3, T_n f(x) is essentially a conditional expectation—i.e., in traditional notation: E( f | X_n = x). How is it that T_n can operate on f(x) and “see” what x is? Either I must take 11.3 to imply that the domain of T_n consists of the range of f, or that the domain of T_n consists of gambles f in L(X_n). Either way, x does not seem to appear as an argument to T_n; it seems to “know” nothing about x. If the first interpretation were correct, then if f was not one-to-one, f(x) could equal f(y) where x != y, and I see no reason to assume that E(f | X_n=x) must always equal E(f | X_n=y). I’m not sure if I’m making myself clear; I’m sure that there’s something I've overlooked, or that I’m misinterpreting some notation or concept.]
Marshall Abrams, Associate Professor Department of Philosophy, University of Alabama at Birmingham http://http://members.logical.net/~marshall Email: mabrams(a)uab.edu; Phone: (205) 996-7483; Fax: (205) 975-6610 Mail: HB 414A, 900 13th Street South, Birmingham, AL 35294-1260; Office: HB 418
SIPTA mailing list SIPTA(a)idsia.ch http://mailman2.ti-edu.ch/mailman/listinfo/sipta
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Sebastien Destercke, Ph. D. CNRS researcher in computer science.