48. New paper by Arnold Shapiro

An introduction to fuzzy random variables, intended for an actuarial science audience.

Arnold F. Shapiro. A fuzzy random variable primer.

It may be worth pointing out that Shapiro was awarded the second-best-presentation award in the 42nd Actuarial Research Conference (August 2007) for this paper.

47. Old book by Edwin Jaynes

I thought the `preprint' version of Jaynes's book had been removed from the Internet when it was published in paper. Either I was wrong, or it is back there anyway. It can be downloaded, chapter by chapter (30 chapters plus 9 appendices), as PS files. Be aware that these files are not final (or they weren't the first time I found them) as Jaynes died before finishing the book, leaving some parts unfinished, and the final version was prepared by Larry Bretthorst.

Edwin T. Jaynes (2003). Probability Theory. The logic of science. Cambdridge Univ. Press, Cambridge.

Sometimes lucid, sometimes irritating, sometimes enlightening, often misguiding.

46. Old theses by Körner, Hébert and myself

I finally found Ralf Körner's thesis

Ralf Körner (1997). Linear models with random fuzzy variables

at his old website at Freiberg. Some preprints can be found there too.

Moreover, I've found P.-A. Hébert's

Pierre-Alexandre Hébert (2004). Analyse de données sensorielles : une approche ordinale floue (Sensorial data analysis: an ordinal fuzzy approach).

It seems fair enough to add my own thesis here, even if it were only to make this really multi-language.

Pedro Terán (2003). Teoremas de aproximación y convergencia para conjuntos y funciones aleatorias (Approximation and convergence theorems for random sets and random functions).

45. Old papers by Thierry Denœux and co-workers

Denœux works, among other things, on fuzzy data analysis. He is one of several people who have started devising methods for fitting fuzzy measures to empirical data.

Some papers of his can be found here at his website.

44. Old paper by Baudrit, Couso and Dubois

Hybrid methods for uncertainty modelling are in their infancy. I suspect we might be missing a whole layer of deeper concepts underlying the familiar notions of probability, possibility, etcetera.

The near future, hierarchical Bayesian modelling rising exponentially, may be dark for some time for realistic approaches. Ideally, we'd need a compelling foundation* which would suggest simple practical implementations, reasonable for practitioners.

Cédric Baudrit, Inés Couso, Didier Dubois (2007). Joint propagation of probability and possibility in risk analysis: towards a formal framework. Int. J. Approx. Reasoning 45, 82-105.


* No, I don't find Bayesian foundations compelling at all.

43. SMPS'08: Deadline extended

The deadline for paper submission to the 4th International Conference on Soft Methods in Probability and Statistics has moved from Feb 1st to Feb 11th.