Synthesis of probability transformers
J. Łąski (1976)
Applicationes Mathematicae
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J. Łąski (1976)
Applicationes Mathematicae
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C. V. Stanojević (1973)
Recherche Coopérative sur Programme n°25
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Mostafa K. Ardakani, Shaun S. Wulff (2014)
Discussiones Mathematicae Probability and Statistics
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Bertrand's paradox is a longstanding problem within the classical interpretation of probability theory. The solutions 1/2, 1/3, and 1/4 were proposed using three different approaches to model the problem. In this article, an extended problem, of which Bertrand's paradox is a special case, is proposed and solved. For the special case, it is shown that the corresponding solution is 1/3. Moreover, the reasons of inconsistency are discussed and a proper modeling approach is determined by...
M. S. Bingham, K. R. Parthasarathy (1966-1967)
Publications mathématiques et informatique de Rennes
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Romano Scozzafava (1996)
Mathware and Soft Computing
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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.
Giulianella Coletti (1996)
Mathware and Soft Computing
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In this paper we present an overview of mathematical models for handling partial entailments and their extensions in a probabilistic frame.
Andrzej Kamiński (1985)
Colloquium Mathematicae
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Locker, Bernard (2009)
Journal Électronique d'Histoire des Probabilités et de la Statistique [electronic only]
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Nguyen Van Hung, Quang Luu Dinh (1989)
Annales scientifiques de l'Université de Clermont-Ferrand 2. Série Probabilités et applications
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Michał Baran (2004)
Applicationes Mathematicae
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The probability minimizing problem for large losses of portfolio in discrete and continuous time models is studied. This gives a generalization of quantile hedging presented in [3].
A. Montanaro, A. Bressan (1983)
Rendiconti del Seminario Matematico della Università di Padova
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