Search results for " Probability"

showing 10 items of 2176 documents

Multivariate Gaussian criteria in SMAA

2006

Abstract We consider stochastic multicriteria decision-making problems with multiple decision makers. In such problems, the uncertainty or inaccuracy of the criteria measurements and the partial or missing preference information can be represented through probability distributions. In many real-life problems the uncertainties of criteria measurements may be dependent. However, it is often difficult to quantify these dependencies. Also, most of the existing methods are unable to handle such dependency information. In this paper, we develop a method for handling dependent uncertainties in stochastic multicriteria group decision-making problems. We measure the criteria, their uncertainties and…

Decision support systemInformation Systems and ManagementGeneral Computer ScienceOperations researchStochastic processStochastic modellingContext (language use)Management Science and Operations ResearchIndustrial and Manufacturing Engineeringsymbols.namesakeJoint probability distributionModeling and SimulationStochastic simulationsymbolsProbability distributionGaussian processMathematicsEuropean Journal of Operational Research
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Probabilistic Logic under Coherence‚ Model−Theoretic Probabilistic Logic‚ and Default Reasoning in System P

2016

We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore how probabilistic reasoning under coherence is related to model-theoretic probabilistic reasoning and to default reasoning in System P. In particular, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Moreover, we show that probabilistic reasoning under coherence is a generalization of default reasoning in System P. That is, we provide a new probabilistic semantics for System P, which neither uses infinitesimal probabilities nor atomic bound (or bi…

Deductive reasoningSettore MAT/06 - Probabilita' E Statistica MatematicaConditional probability assessments conditional constraints probabilistic logic under coherence model-theoretic probabilistic logic g-coherence g-coherent entailment defaultreasoning from conditional knowledge bases System P conditional objects.conditional constraintsLogicDefault logicStatistics::Other StatisticsProbabilistic logic networkConditional probability assessmentsprobabilistic logic under coherenceNon-monotonic logicSystem PMathematicsg-coherent entailmentHardware_MEMORYSTRUCTURESmodel-theoretic probabilistic logicbusiness.industryProbabilistic logicSystem P; g-coherence; conditional objectsCoherence (statistics)default reasoning from conditional knowledge basesProbabilistic argumentationConditional probability assessments; conditional constraints; probabilistic logic under coherence; model-theoretic probabilistic logic; g-coherence; g-coherent entailment; default reasoning from conditional knowledge bases; System P; conditional objects.Philosophyg-coherenceProbabilistic CTLArtificial intelligencebusinessAlgorithmconditional objectsJournal of Applied Non−Classical Logics
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Probabilistic Logic under Coherence, Model-Theoretic Probabilistic Logic, and Default Reasoning

2001

We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore the relationship between coherence-based and model-theoretic probabilistic logic. Interestingly, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Crucially, we even show that probabilistic reasoning under coherence is a probabilistic generalization of default reasoning in system P. That is, we provide a new probabilistic semantics for system P, which is neither based on infinitesimal probabilities nor on atomic-bound (or also big-stepped) probabil…

Deductive reasoningSettore MAT/06 - Probabilita' E Statistica MatematicaKnowledge representation and reasoningComputer scienceDefault logicDivergence-from-randomness modelLogic modelcomputer.software_genreLogical consequenceProbabilistic logic networkConditional probability assessments conditional constraints probabilistic logic under coherence model-theoretic probabilistic logic g-coherence g-coherent entailment default reasoning from conditional knowledge bases System P conditional objectsprobabilistic logic under coherenceNon-monotonic logicProbabilistic relevance modeldefault reasoningmodel-theoretic probabilistic logicbusiness.industryProbabilistic logicProbabilistic argumentationExpert systemg-coherencesystem pProbabilistic CTLArtificial intelligencebusinesscomputerdefault reasoning; g-coherence; model-theoretic probabilistic logic; probabilistic logic under coherence; system p
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Bounds for the relative n-th nilpotency degree in compact groups

2009

The line of investigation of the present paper goes back to a classical work of W. H. Gustafson of the 1973, in which it is described the probability that two randomly chosen group elements commute. In the same work, he gave some bounds for this kind of probability, providing information on the group structure. We have recently obtained some generalizations of his results for finite groups. Here we improve them in the context of the compact groups.

Degree (graph theory)Group (mathematics)General MathematicsProbability (math.PR)20P05 22A05 28C10 22A20 43A05Context (language use)Group Theory (math.GR)Group structureCombinatoricsLine (geometry)FOS: MathematicsMathematics - Group TheoryMathematics - ProbabilityHaar measureMathematics
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Space-Time FPCA Clustering of Multidimensional Curves.

2018

In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure, applying a variant of a k-means algorithm based on the principal component rotation of data. The main advantage of this approach is to combine the clustering functional analysis of the multidimensional data, with smoothing methods based on generalized additive models, that cope with both the spatial and the temporal variability, and with functional principal components that takes into account the dependency between the curves.

Dependency (UML)Computer sciencebusiness.industryClustering of multidimensional curves GAM Spatio-temporal patternSpace timeGeneralized additive modelPattern recognition010502 geochemistry & geophysics01 natural sciences010104 statistics & probabilityPrincipal component analysisArtificial intelligence0101 mathematicsCluster analysisbusinessFocus (optics)Settore SECS-S/01 - StatisticaRotation (mathematics)Smoothing0105 earth and related environmental sciences
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The Effective Sample Size

2013

Model selection procedures often depend explicitly on the sample size n of the experiment. One example is the Bayesian information criterion (BIC) criterion and another is the use of Zellner–Siow priors in Bayesian model selection. Sample size is well-defined if one has i.i.d real observations, but is not well-defined for vector observations or in non-i.i.d. settings; extensions of critera such as BIC to such settings thus requires a definition of effective sample size that applies also in such cases. A definition of effective sample size that applies to fairly general linear models is proposed and illustrated in a variety of situations. The definition is also used to propose a suitable ‘sc…

Deviance information criterionEconomics and EconometricsBayesian information criterionSample size determinationModel selectionPrior probabilityStatisticsLinear modelBayesian inferenceAlgorithmSelection (genetic algorithm)Statistics::ComputationMathematicsEconometric Reviews
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Introducing randomness in the analysis of chemical reactions: An analysis based on random differential equations and probability density functions

2021

[EN] In this work we consider a particular randomized kinetic model for reaction-deactivation of hydrogen peroxide decomposition. We apply the Random Variable Transformation technique to obtain the first probability density function of the solution stochastic process under general conditions. From the rst probability density function, we can obtain fundamental statistical information, such as the mean and the variance of the solution, at every instant time. The transformation considered in the application of the Random Variable Transformation technique is not unique. Then, the first probability density function can take different expressions, although essentially equivalent in terms of comp…

Differential equationComputational MechanicsRandom modelProbability density functionChemical reactionComputational MathematicsComputational Theory and MathematicsChemical kinetic modelRandom modelRandom variable transformation techniqueFirst probability density functionStatistical physicsMATEMATICA APLICADARandomnessMathematicsComputational and Mathematical Methods
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Solving fully randomized higher-order linear control differential equations: Application to study the dynamics of an oscillator

2021

[EN] In this work, we consider control problems represented by a linear differential equation assuming that all the coefficients are random variables and with an additive control that is a stochastic process. Specifically, we will work with controllable problems in which the initial condition and the final target are random variables. The probability density function of the solution and the control has been calculated. The theoretical results have been applied to study, from a probabilistic standpoint, a damped oscillator.

Differential equationDynamics (mechanics)Computational MechanicsRandom damped linear oscillatorsRandom control differential equationComputational MathematicsComputational Theory and MathematicsRandom variable transformation techniqueApplied mathematicsOrder (group theory)First probability density functionMATEMATICA APLICADALinear controlMathematics
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Levy targeting and the principle of detailed balance

2011

We investigate confining mechanisms for Lévy flights under premises of the principle of detailed balance. In this case, the master equation of the jump-type process admits a transformation to the Lévy-Schrödinger semigroup dynamics akin to a mapping of the Fokker-Planck equation into the generalized diffusion equation. This sets a correspondence between above two stochastic dynamical systems, within which we address a (stochastic) targeting problem for an arbitrary stability index μ ε (0,2) of symmetric Lévy drivers. Namely, given a probability density function, specify the semigroup potential, and thence the jump-type dynamics for which this PDF is actually a long-time asymptotic (target) …

Diffusion equationDynamical systems theoryMovementNormal DistributionFOS: Physical sciencesDiffusionOscillometryMaster equationFOS: MathematicsApplied mathematicsCondensed Matter - Statistical MechanicsMathematical PhysicsMathematicsStochastic ProcessesModels StatisticalStatistical Mechanics (cond-mat.stat-mech)SemigroupStochastic processPhysicsProbability (math.PR)Mathematical analysisCauchy distributionDetailed balanceMathematical Physics (math-ph)Markov ChainsTransformation (function)ThermodynamicsAlgorithmsMathematics - Probability
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Anisotropic -Laplacian equations when goes to

2010

Abstract In this paper we prove a stability result for an anisotropic elliptic problem. More precisely, we consider the Dirichlet problem for an anisotropic equation, which is as the p -Laplacian equation with respect to a group of variables and as the q -Laplacian equation with respect to the other variables ( 1 p q ), with datum f belonging to a suitable Lebesgue space. For this problem, we study the behaviour of the solutions as p goes to 1 , showing that they converge to a function u , which is almost everywhere finite, regardless of the size of the datum f . Moreover, we prove that this u is the unique solution of a limit problem having the 1-Laplacian operator with respect to the firs…

Dirichlet problemGroup (mathematics)Applied MathematicsMathematical analysisp-LaplacianStandard probability spaceAlmost everywhereFunction (mathematics)Limit (mathematics)Laplace operatorAnalysisMathematicsNonlinear Analysis: Theory, Methods & Applications
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