Displaying similar documents to “Translation invariance and finite additivity in a probability measure on the natural numbers.”

The Relevance of Measure and Probability, and Definition of Completeness of Probability

Bo Zhang, Hiroshi Yamazaki, Yatsuka Nakamura (2006)

Formalized Mathematics

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In this article, we first discuss the relation between measure defined using extended real numbers and probability defined using real numbers. Further, we define completeness of probability, and its completion method, and also show that they coincide with those of measure.

Alternative definitions of conditional possibilistic measures

Ivan Kramosil (1998)

Kybernetika

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The aim of this paper is to survey and discuss, very briefly, some ways how to introduce, within the framework of possibilistic measures, a notion analogous to that of conditional probability measure in probability theory. The adjective “analogous” in the last sentence is to mean that the conditional possibilistic measures should play the role of a mathematical tool to actualize one’s degrees of beliefs expressed by an a priori possibilistic measure, having obtained some further information...

Equivalent or absolutely continuous probability measures with given marginals

Patrizia Berti, Luca Pratelli, Pietro Rigo, Fabio Spizzichino (2015)

Dependence Modeling

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Let (X,A) and (Y,B) be measurable spaces. Supposewe are given a probability α on A, a probability β on B and a probability μ on the product σ-field A ⊗ B. Is there a probability ν on A⊗B, with marginals α and β, such that ν ≪ μ or ν ~ μ ? Such a ν, provided it exists, may be useful with regard to equivalent martingale measures and mass transportation. Various conditions for the existence of ν are provided, distinguishing ν ≪ μ from ν ~ μ.

Robust inference in probability under vague information.

Giuliana Regoli (1996)

Mathware and Soft Computing

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Vague information can be represented as comparison of previsions or comparison of probabilities, and a robust analysis can be done, in order to make inference about some quantity of interest and to measure the imprecision of the answers. In particular, in some decision problems the answer can be unique.