Search results for "Conditional prevision"

showing 7 items of 7 documents

Iterated Conditionals and Characterization of P-Entailment

2021

In this paper we deepen, in the setting of coherence, some results obtained in recent papers on the notion of p-entailment of Adams and its relationship with conjoined and iterated conditionals. We recall that conjoined and iterated conditionals are suitably defined in the framework of conditional random quantities. Given a family \(\mathcal {F}\) of n conditional events \(\{E_{1}|H_{1},\ldots , E_{n}|H_{n}\}\) we denote by \(\mathcal {C}(\mathcal {F})=(E_{1}|H_{1})\wedge \cdots \wedge (E_{n}|H_{n})\) the conjunction of the conditional events in \(\mathcal F\). We introduce the iterated conditional \(\mathcal {C}(\mathcal {F}_{2})|\mathcal {C}(\mathcal {F}_{1})\), where \(\mathcal {F}_{1}\)…

CombinatoricsPhysicsSettore MAT/06 - Probabilita' E Statistica MatematicaCoherence Conditional events Conditional random quantitiesConditional previsions Conjoined conditionals Iterated conditionalsProbabilistic entailment.Iterated functionProduct (mathematics)Characterization (mathematics)
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On general conditional prevision assessments

2009

In this paper we consider general conditional random quantities of the kind $X|Y$, where $X$ and $Y$ are finite discrete random quantities. Then, we introduce the notion of coherence for conditional prevision assessments on finite families of general conditional random quantities. Moreover, we give a compound prevision theorem and we examine the relation between the previsions of $X|Y$ and $Y|X$. Then, we give some results on random gains and, by a suitable alternative theorem, we obtain a characterization of coherence. We also propose an algorithm for the checking of coherence. Finally, we briefly examine the case of imprecise conditional prevision assessments by introducing the notions of…

Conditional random quantities; coherence; conditional prevision assessments; random gain; alternative theorems; algorithms; imprecise assessments; generalized and total coherence.Settore MAT/06 - Probabilita' E Statistica Matematicarandom gainConditional events general conditional random quantitiesgeneral conditional prevision assessments generalized compound prevision theorem generalized Bayes TheoremConditional random quantitiesalgorithmsimprecise assessmentsalternative theoremsgeneralized and total coherencecoherenceconditional prevision assessments
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Compound conditionals, Fr\'echet-Hoeffding bounds, and Frank t-norms

2021

Abstract In this paper we consider compound conditionals, Frechet-Hoeffding bounds and the probabilistic interpretation of Frank t-norms. By studying the solvability of suitable linear systems, we show under logical independence the sharpness of the Frechet-Hoeffding bounds for the prevision of conjunctions and disjunctions of n conditional events. In addition, we illustrate some details in the case of three conditional events. We study the set of all coherent prevision assessments on a family containing n conditional events and their conjunction, by verifying that it is convex. We discuss the case where the prevision of conjunctions is assessed by Lukasiewicz t-norms and we give explicit s…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaLogical independenceFrank t-normsApplied MathematicsLinear systemProbabilistic logicRegular polygon02 engineering and technologyConjunction and disjunctionConditional previsionTheoretical Computer ScienceConvexityFréchet-Hoeffding boundArtificial Intelligence020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPairwise comparisonCoherenceSoftwareMathematics - ProbabilityCounterexampleMathematicsCorresponding conditional
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Conditional Random Quantities and Iterated Conditioning in the Setting of Coherence

2013

We consider conditional random quantities (c.r.q.’s) in the setting of coherence. Given a numerical r.q. X and a non impossible event H, based on betting scheme we represent the c.r.q. X|H as the unconditional r.q. XH + μH c , where μ is the prevision assessed for X|H. We develop some elements for an algebra of c.r.q.’s, by giving a condition under which two c.r.q.’s X|H and Y|K coincide. We show that X|HK coincides with a suitable c.r.q. Y|K and we apply this representation to Bayesian updating of probabilities, by also deepening some aspects of Bayes’ formula. Then, we introduce a notion of iterated c.r.q. (X|H)|K, by analyzing its relationship with X|HK. Our notion of iterated conditiona…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaSettore INF/01 - Informaticaconditional random quantitiesCoherence (statistics)Bayesian inferencebayesian updatingcoherenceCombinatoricsconditional previsionsBayes' theoremIterated functionbayesian updating; conditional random quantities; betting scheme; conditional previsions; coherence; iterated conditioning; iterated conditioning.Coherence betting scheme conditional random quantities conditional previsions Bayesian updating iterated conditioning.Scheme (mathematics)iterated conditioningConditioningRepresentation (mathematics)betting schemeEvent (probability theory)Mathematics
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Iterated Conditionals, Trivalent Logics, and Conditional Random Quantities

2022

We consider some notions of iterated conditionals by checking the validity of some desirable basic logical and probabilistic properties, which are valid for simple conditionals. We consider de Finetti’s notion of conditional as a three-valued object and as a conditional random quantity in the betting framework. We recall the notions of conjunction and disjunction among conditionals in selected trivalent logics. Then, we analyze the two notions of iterated conditional introduced by Calabrese and de Finetti, respectively. We show that the compound probability theorem and other basic properties are not preserved by these objects, by also computing some probability propagation rules. Then, for …

Settore MAT/06 - Probabilita' E Statistica MatematicaCoherence Conditional events Conditional random quantities Conditional previsions Conjoined and disjoined conditionals Iterated conditionals Compound probability theorem Lower and upper bounds Import-export principle
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Coherent Conditional Previsions and Proper Scoring Rules

2012

In this paper we study the relationship between the notion of coherence for conditional prevision assessments on a family of finite conditional random quantities and the notion of admissibility with respect to bounded strictly proper scoring rules. Our work extends recent results given by the last two authors of this paper on the equivalence between coherence and admissibility for conditional probability assessments. In order to prove that admissibility implies coherence a key role is played by the notion of Bregman divergence.

Settore MAT/06 - Probabilita' E Statistica Matematicabregman divergenceproper scor- ing rulesConditional prevision assessmentsconditional scoring rulesstrong dominanceConditional probabilityweak dominanceCoherence (statistics)Bregman divergenceConditional prevision assessments coherence proper scoring rules conditional scoring rules weak dominance strong dominance admissibility Bregman divergence.proper scoring rulescoherenceBounded functionKey (cryptography)admissibilityConditional prevision assessments; conditional scoring rules; admissibility; proper scor- ing rules; weak dominance; strong dominanceEquivalence (measure theory)Mathematical economicsconditional prevision assessments; strong dominance; admissibility; proper scoring rules; bregman divergence; weak dominance; conditional scoring rules; coherenceMathematics
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On general conditional random quantities

2009

In the first part of this paper, recalling a general discussion on iterated conditioning given by de Finetti in the appendix of his book, vol. 2, we give a representation of a conditional random quantity $X|HK$ as $(X|H)|K$. In this way, we obtain the classical formula $\pr{(XH|K)} =\pr{(X|HK)P(H|K)}$, by simply using linearity of prevision. Then, we consider the notion of general conditional prevision $\pr(X|Y)$, where $X$ and $Y$ are two random quantities, introduced in 1990 in a paper by Lad and Dickey. After recalling the case where $Y$ is an event, we consider the case of discrete finite random quantities and we make some critical comments and examples. We give a notion of coherence fo…

Settore MAT/06 - Probabilita' E Statistica Matematicageneral conditional random quantities; general conditional prevision assessments; generalized compound prevision theoremgeneral conditional prevision assessmentsiterated conditioninggeneralized compound prevision theoremgeneral conditional random quantitiesconditional eventsstrong generalized compound prevision theoremConditional events general conditional random quantities general conditional prevision assessments generalized compound prevision theorem iterated conditioning strong generalized compound prevision theoremconditional events; general conditional random quantities; general conditional prevision assessments; generalized compound prevision theorem; iterated conditioning; strong generalized compound prevision theorem.
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