617 research outputs found

    On the existence of the true value of a probability. Part 2: The representation theorem and the ergodic theory

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    Some authors, basing their ideas on the exchangeability property, on the postulates of the representation theorem and on its interpretation in the ambit of ergodic theory, believed to find a counterexample to the subjectivist model through the theoretical justification of the existence of an objective probability. As a proof of the inconsistency of this reasoning, the representation theorem allows to assert that the convergence of the relative frequency on a “true value” of the probability is only a metaphysical illusion motivated by an asymptotic behaviour of the personal assessments of initial probabilities, leading to intersubjective assignment. With regard to the ergodic theory, its assimilation to the propensity model allows the demonstration of its metaphysical character and the resulting subjectivity in the assignment f probabilities.

    A Conversation with Eugenio Regazzini

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    Eugenio Regazzini was born on August 12, 1946 in Cremona (Italy), and took his degree in 1969 at the University "L. Bocconi" of Milano. He has held positions at the universities of Torino, Bologna and Milano, and at the University "L. Bocconi" as assistant professor and lecturer from 1974 to 1980, and then professor since 1980. He is currently professor in probability and mathematical statistics at the University of Pavia. In the periods 1989-2001 and 2006-2009 he was head of the Institute for Applications of Mathematics and Computer Science of the Italian National Research Council (C.N.R.) in Milano and head of the Department of Mathematics at the University of Pavia, respectively. For twelve years between 1989 and 2006, he served as a member of the Scientific Board of the Italian Mathematical Union (U.M.I.). In 2007, he was elected Fellow of the IMS and, in 2001, Fellow of the "Istituto Lombardo---Accademia di Scienze e Lettere." His research activity in probability and statistics has covered a wide spectrum of topics, including finitely additive probabilities, foundations of the Bayesian paradigm, exchangeability and partial exchangeability, distribution of functionals of random probability measures, stochastic integration, history of probability and statistics. Overall, he has been one of the most authoritative developers of de Finetti's legacy. In the last five years, he has extended his scientific interests to probabilistic methods in mathematical physics; in particular, he has studied the asymptotic behavior of the solutions of equations, which are of interest for the kinetic theory of gases. The present interview was taken in occasion of his 65th birthday.Comment: Published in at http://dx.doi.org/10.1214/11-STS362 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Behavioural Economics: Classical and Modern

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    In this paper, the origins and development of behavioural economics, beginning with the pioneering works of Herbert Simon (1953) and Ward Edwards (1954), is traced, described and (critically) discussed, in some detail. Two kinds of behavioural economics – classical and modern – are attributed, respectively, to the two pioneers. The mathematical foundations of classical behavioural economics is identified, largely, to be in the theory of computation and computational complexity; the corresponding mathematical basis for modern behavioural economics is, on the other hand, claimed to be a notion of subjective probability (at least at its origins in the works of Ward Edwards). The economic theories of behavior, challenging various aspects of 'orthodox' theory, were decisively influenced by these two mathematical underpinnings of the two theoriesClassical Behavioural Economics, Modern Behavioural Economics, Subjective Probability, Model of Computation, Computational Complexity. Subjective Expected Utility

    Subjective probability, trivalent logics and compound conditionals

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    In this work we first illustrate the subjective theory of de Finetti. We recall the notion of coherence for both the betting scheme and the penalty criterion, by considering the unconditional and conditional cases. We show the equivalence of the two criteria by giving the geometrical interpretation of coherence. We also consider the notion of coherence based on proper scoring rules. We discuss conditional events in the trivalent logic of de Finetti and the numerical representation of truth-values. We check the validity of selected basic logical and probabilistic properties for some trivalent logics: Kleene-Lukasiewicz-Heyting-de Finetti; Lukasiewicz; Bochvar-Kleene; Sobocinski. We verify that none of these logics satisfies all the properties. Then, we consider our approach to conjunction and disjunction of conditional events in the setting of conditional random quantities. We verify that all the basic logical and probabilistic properties (included the Fr\'{e}chet-Hoeffding bounds) are preserved in our approach. We also recall the characterization of p-consistency and p-entailment by our notion of conjunction

    Teaching statistics in the physics curriculum: Unifying and clarifying role of subjective probability

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    Subjective probability is based on the intuitive idea that probability quantifies the degree of belief that an event will occur. A probability theory based on this idea represents the most general framework for handling uncertainty. A brief introduction to subjective probability and Bayesian inference is given, with comments on typical misconceptions which tend to discredit it and comparisons to other approaches.Comment: 15 pages, LateX, 1 eps figure, corrected some typos. Invited paper for the American Journal of Physics. This paper and related work are also available at http://www-zeus.roma1.infn.it/~agostini

    You May Believe You Are a Bayesian But You Are Probably Wrong

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    An elementary sketch of some issues in statistical inference and in particular of the central role of likelihood is given. This is followed by brief outlines of what George Barnard considered were the four great systems of statistical inferences. These can be thought of terms of the four combinations of two factors at two levels. The first is fundamental purpose (decision or inference) and the second probability argument (direct or inverse). Of these four systems the 'fully Bayesiani approach of decision- making using inverse probability particularly associated with the Ramsay, De Finetti, Savage and Lindley has some claims to be the most impressive. It is claimed, however, and illustrated by example, that this approach seems to be impossible to follow. It is speculated that there may be some advantage to the practising statistician to follow George Barnardis advice of being familiar with all four systems.philosophy of statistics, decision theory, likelihood, subjective probability, Bayesianism, Bayes theorem, Fisher, Neyman and Pearson, Jeffreys

    On quantum vs. classical probability

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    Quantum theory shares with classical probability theory many important properties. I show that this common core regards at least the following six areas, and I provide details on each of these: the logic of propositions, symmetry, probabilities, composition of systems, state preparation and reductionism. The essential distinction between classical and quantum theory, on the other hand, is shown to be joint decidability versus smoothness; for the latter in particular I supply ample explanation and motivation. Finally, I argue that beyond quantum theory there are no other generalisations of classical probability theory that are relevant to physics.Comment: Major revision: key results unchanged, but derivation and discussion completely rewritten; 33 pages, no figure
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