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The definition of the conditional probability is very important in the theory of the probability. This definition is based on the fact, that random events can be simultaneously measurable. This paper deal with the problem of conditioning…

Mathematical Physics · Physics 2009-11-10 Olga Nanasiova

In this comprehensive study, we delve deeply into the concept of multivariate total positivity, defining it in accordance with a direction. We rigorously explore numerous salient properties, shedding light on the nuances that characterize…

Statistics Theory · Mathematics 2025-01-16 Enrique de Amo , José Juan Quesada-Molina , Manuel Úbeda-Flores

In this review article we present different formal frameworks for the description of generalized probabilities in statistical theories. We discuss the particular cases of probabilities appearing in classical and quantum mechanics, possible…

Other Statistics · Statistics 2021-08-04 F. Holik , C. Massri , A. Plastino , M. Sáenz

A new formulation of quantum mechanics is proposed based on a new principle that can be considered a generalization of the Born rule. The principle is composed of a mathematical expression and an associated interpretation, and establishes a…

Quantum Physics · Physics 2008-10-31 Bruno Galvan

A rigorous general definition of quantum probability is given, which is valid for elementary events and for composite events, for operationally testable measurements as well as for inconclusive measurements, and also for non-commuting…

Quantum Physics · Physics 2016-01-12 V. I. Yukalov , D. Sornette

In this paper we introduce the so-called Generalized Naive Bayes structure as an extension of the Naive Bayes structure. We give a new greedy algorithm that finds a good fitting Generalized Naive Bayes (GNB) probability distribution. We…

Machine Learning · Statistics 2024-08-29 Edith Alice Kovács , Anna Ország , Dániel Pfeifer , András Benczúr

This paper studies preference aggregation under uncertainty in the multi-profile framework and characterizes a new class of aggregation rules that address classical concerns about Harsanyi's (1955) utilitarian rules. Our aggregation rules,…

Theoretical Economics · Economics 2026-05-12 Leo Kurata , Kensei Nakamura

A general approach is established for deriving one-shot performance bounds for information-theoretic problems on general alphabets beyond countable alphabets. It is mainly based on the quantization idea and a novel form of "likelihood…

Information Theory · Computer Science 2016-07-12 Shengtian Yang , Thomas Honold , Zhaoyang Zhang

The propositional logic is generalized on the real numbers field. the logical function with all properties of the classical probability function is obtained. The logical analog of the Bernoulli independent tests scheme is constructed. The…

General Mathematics · Mathematics 2007-05-23 G. A. Quznetsov

In a language corpus, the probability that a word occurs $n$ times is often proportional to $1/n^2$. Assigning rank, $s$, to words according to their abundance, $\log s$ vs $\log n$ typically has a slope of minus one. That simple Zipf's law…

Populations and Evolution · Quantitative Biology 2019-03-27 Steven A. Frank

We examine the issue of stability of probability in reasoning about complex systems with uncertainty in structure. Normally, propositions are viewed as probability functions on an abstract random graph where it is implicitly assumed that…

Artificial Intelligence · Computer Science 2017-12-14 Subhash Kak

Recent work in cognitive science has uncovered a diversity of explanatory values, or dimensions along which we judge explanations as better or worse. We propose a Bayesian account of how these values fit together to guide explanation. The…

Neurons and Cognition · Quantitative Biology 2020-10-29 Zachary Wojtowicz , Simon DeDeo

This paper gives game-theoretic versions of several results on "merging of opinions" obtained in measure-theoretic probability and algorithmic randomness theory. An advantage of the game-theoretic versions over the measure-theoretic results…

Probability · Mathematics 2007-05-23 Vladimir Vovk

We introduce a new approach to modeling uncertainty based on plausibility measures. This approach is easily seen to generalize other approaches to modeling uncertainty, such as probability measures, belief functions, and possibility…

Artificial Intelligence · Computer Science 2016-08-31 Nir Friedman , Joseph Y. Halpern

McFadden and Richter (1991) and later McFadden (2005) show that the Axiom of Revealed Stochastic Preference characterizes rationalizability of choice probabilities through random utility models on finite universal choice spaces. This note…

Theoretical Economics · Economics 2019-02-21 Jörg Stoye

McGranaghan, Nielsen, O'Donoghue, Somerville, and Sprenger [2024] show that standard paired choice tests for the common ratio effect are structurally biased when choice is stochastic, proposing valuation tests as a robust alternative. Using…

Theoretical Economics · Economics 2026-04-14 Federico Echenique , Gerelt Tserenjigmid

An agent observes a clue, and an analyst observes an inference: a ranking of events on the basis of how corroborated they are by the clue. We prove that if the inference satisfies the axioms of Villegas (1964) except for the classic…

Theoretical Economics · Economics 2025-11-04 Andrew Mackenzie

In this work, we develop a formal system of inductive logic. It uses an infinitary language that allows for countable conjunctions and disjunctions. It is based on a set of nine syntactic rules of inductive inference, and contains classical…

Probability · Mathematics 2025-05-01 Jason Swanson

Several characterizations of the Generalized Inverse Gaussian (GIG) distribution have been proposed in the literature, especially over the past two decades. These characterization theorems are surveyed, and two new characterizations are…

Probability · Mathematics 2013-12-30 Angelo Efoevi Koudou , Christophe Ley

Computing reachability probabilities is a fundamental problem in the analysis of probabilistic programs. This paper aims at a comprehensive and comparative account on various martingale-based methods for over- and under-approximating…

Programming Languages · Computer Science 2018-11-16 Toru Takisaka , Yuichiro Oyabu , Natsuki Urabe , Ichiro Hasuo
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