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Most of the stochastic orders for comparing random variables, considered in the literature, are afflicted with two main drawbacks: (i) lack of connex property and (ii) lack of consideration of any dependence structure between the random…

Methodology · Statistics 2021-03-03 Sugata Ghosh , Asok K. Nanda

Possibility theory offers a framework where both Lehmann's "preferential inference" and the more productive (but less cautious) "rational closure inference" can be represented. However, there are situations where the second inference does…

Artificial Intelligence · Computer Science 2013-02-18 Salem Benferhat , Didier Dubois , Henri Prade

In this paper, we prove a conditional limit theorem for independent not necessarily identically distributed random variables. Namely, we obtain the asymptotic distribution of a large number of them given the sum.

Statistics Theory · Mathematics 2020-11-12 Dimbihery Rabenoro

The standard odds ratio of logistic regression is foundational but limited to individual explanatory variables. This work derives a multivariable odds ratio that applies to all the explanatory variables in all their combinations.

Methodology · Statistics 2025-04-25 José Raúl Martínez

Conventional multiclass conditional probability estimation methods, such as Fisher's discriminate analysis and logistic regression, often require restrictive distributional model assumption. In this paper, a model-free estimation method is…

Machine Learning · Statistics 2013-08-02 Tu Xu , Junhui Wang

The Contextuality-by-Default approach to determining and measuring the (non)contextuality of a system of random variables requires that every random variable in the system be represented by an equivalent set of dichotomous random variables.…

Quantum Physics · Physics 2022-01-05 Janne V. Kujala , Ehtibar N. Dzhafarov

One of the key challenges when looking for the causes of a complex event is to determine the causal status of factors that are neither individually necessary nor individually sufficient to produce that event. In order to reason about how…

Artificial Intelligence · Computer Science 2017-10-11 Sjur K Dyrkolbotn

A general notion of algebraic conditional plausibility measures is defined. Probability measures, ranking functions, possibility measures, and (under the appropriate definitions) sets of probability measures can all be viewed as defining…

Artificial Intelligence · Computer Science 2014-07-29 Joseph Y. Halpern

We propose a combination of probabilistic reasoning from conditional constraints with approaches to default reasoning from conditional knowledge bases. In detail, we generalize the notions of Pearl's entailment in system Z, Lehmann's…

Artificial Intelligence · Computer Science 2007-05-23 Thomas Lukasiewicz

A causal set is a partially ordered set on a countably infinite ground-set such that each element is above finitely many others. A natural extension of a causal set is an enumeration of its elements which respects the order. We bring…

Probability · Mathematics 2011-09-22 Graham Brightwell , Malwina Luczak

The common cause principle for two random variables $A$ and $B$ is examined in the case of causal insufficiency, when their common cause $C$ is known to exist, but only the joint probability of $A$ and $B$ is observed. As a result, $C$…

Data Analysis, Statistics and Probability · Physics 2024-07-26 A. Hovhannisyan , A. E. Allahverdyan

We present a propositional logic to reason about the uncertainty of events, where the uncertainty is modeled by a set of probability measures assigning an interval of probability to each event. We give a sound and complete axiomatization…

Artificial Intelligence · Computer Science 2014-08-08 Joseph Y. Halpern , Riccardo Pucella

This paper develops a trivalent semantics for the truth conditions and the probability of the natural language indicative conditional. Our framework rests on trivalent truth conditions first proposed by W. Cooper and yields two logics of…

Artificial Intelligence · Computer Science 2023-05-01 Paul Égré , Lorenzo Rossi , Jan Sprenger

The compositeness $X$ is defined as the probability to observe the composite structure such as the hadronic molecule component in a bound state. One of the model-independent approaches to calculate $X$ is the weak-binding relation. However,…

High Energy Physics - Phenomenology · Physics 2022-11-30 Tomona Kinugawa , Tetsuo Hyodo

A non-classical formulation of the central limit theorem is given for sequences of independent random variables with finite second moments. Singular sequences whose members all have a degenerate or normal distribution are excluded from…

Probability · Mathematics 2025-01-29 Alexander Shmyrov , Vasily Shmyrov

We develop a new method for generating prediction sets that combines the flexibility of conformal methods with an estimate of the conditional distribution $P_{Y \mid X}$. Existing methods, such as conformalized quantile regression and…

Machine Learning · Statistics 2024-10-10 Vincent Plassier , Alexander Fishkov , Mohsen Guizani , Maxim Panov , Eric Moulines

Conditionals play a key role in different areas of logic and probabilistic reasoning, and they have been studied and formalized from different angles. In this paper we focus on the de Finetti's notion of conditional as a three-valued…

Logic · Mathematics 2022-05-09 Tommaso Flaminio , Angelo Gilio , Lluis Godo , Giuseppe Sanfilippo

We establish a central limit theorem and an invariance principle for stationary random fields, with projective-type conditions. Our result is obtained via an m-dependent approximation method. As applications, we establish invariance…

Probability · Mathematics 2012-04-12 Yizao Wang , Michael Woodroofe

Many writers have observed that default logics appear to contain the "lottery paradox" of probability theory. This arises when a default "proof by contradiction" lets us conclude that a typical X is not a Y where Y is an unusual subclass of…

Artificial Intelligence · Computer Science 2013-04-08 Eric Neufeld , J. D. Horton

In this paper we recall some results for conditional events, compound conditionals, conditional random quantities, p-consistency, and p-entailment. Then, we show the equivalence between bets on conditionals and conditional bets, by…

Artificial Intelligence · Computer Science 2025-02-11 Angelo Gilio , David E. Over , Niki Pfeifer , Giuseppe Sanfilippo
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