Search results for "calculu"

showing 10 items of 642 documents

Fractional generalized cumulative entropy and its dynamic version

2021

Following the theory of information measures based on the cumulative distribution function, we propose the fractional generalized cumulative entropy, and its dynamic version. These entropies are particularly suitable to deal with distributions satisfying the proportional reversed hazard model. We study the connection with fractional integrals, and some bounds and comparisons based on stochastic orderings, that allow to show that the proposed measure is actually a variability measure. The investigation also involves various notions of reliability theory, since the considered dynamic measure is a suitable extension of the mean inactivity time. We also introduce the empirical generalized fract…

FOS: Computer and information sciencesExponential distributionComputer Science - Information TheoryMathematics - Statistics TheoryStatistics Theory (math.ST)01 natural sciencesMeasure (mathematics)010305 fluids & plasmas0103 physical sciencesFOS: MathematicsApplied mathematicsAlmost surelyCumulative entropy; Fractional calculus; Stochastic orderings; EstimationEntropy (energy dispersal)010306 general physicsStochastic orderingsMathematicsCentral limit theoremNumerical AnalysisInformation Theory (cs.IT)Applied MathematicsCumulative distribution functionProbability (math.PR)Fractional calculusEmpirical measureFractional calculusModeling and SimulationEstimationCumulative entropyMathematics - ProbabilityCommunications in Nonlinear Science and Numerical Simulation
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Fractional Spectral Moments for Digital Simulation of Multivariate Wind Velocity Fields

2012

In this paper, a method for the digital simulation of wind velocity fields by Fractional Spectral Moment function is proposed. It is shown that by constructing a digital filter whose coefficients are the fractional spectral moments, it is possible to simulate samples of the target process as superposition of Riesz fractional derivatives of a Gaussian white noise processes. The key of this simulation technique is the generalized Taylor expansion proposed by the authors. The method is extended to multivariate processes and practical issues on the implementation of the method are reported.

FOS: Computer and information sciencesMultivariate wind velocity fieldMultivariate statisticsStatistical Mechanics (cond-mat.stat-mech)Fractional spectral momentRenewable Energy Sustainability and the EnvironmentMechanical EngineeringMathematical analysisFOS: Physical sciencesGeneralized Taylor formWhite noiseFunction (mathematics)Digital simulation of Gaussian stationary processeFractional calculuStatistics - ComputationTransfer functionWind speedFractional calculusSuperposition principleSettore ICAR/08 - Scienza Delle CostruzioniComputation (stat.CO)Condensed Matter - Statistical MechanicsLinear filterCivil and Structural EngineeringMathematics
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Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-Based Approach

2021

Causal effect identification considers whether an interventional probability distribution can be uniquely determined without parametric assumptions from measured source distributions and structural knowledge on the generating system. While complete graphical criteria and procedures exist for many identification problems, there are still challenging but important extensions that have not been considered in the literature. To tackle these new settings, we present a search algorithm directly over the rules of do-calculus. Due to generality of do-calculus, the search is capable of taking more advanced data-generating mechanisms into account along with an arbitrary type of both observational and…

FOS: Computer and information sciencesStatistics and ProbabilityComputer Science - Machine LearningcausalityComputer Science - Artificial IntelligenceHeuristic (computer science)Computer scienceeducationMachine Learning (stat.ML)transportabilitycomputer.software_genre01 natural sciencesMachine Learning (cs.LG)R-kielimissing dataQA76.75-76.765; QA273-280010104 statistics & probabilitydo-calculuscausality; do-calculus; selection bias; transportability; missing data; case-control design; meta-analysisStatistics - Machine LearningSearch algorithmselection bias0101 mathematicsParametric statisticspäättelymeta-analyysicase-control designhakualgoritmit113 Computer and information sciencesMissing datameta-analysisIdentification (information)Artificial Intelligence (cs.AI)Causal inferencekausaliteettiIdentifiabilityProbability distributionData miningStatistics Probability and UncertaintycomputerSoftwareJournal of Statistical Software
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A novel exact representation of stationary colored Gaussian processes (fractional differential approach)

2010

A novel representation of functions, called generalized Taylor form, is applied to the filtering of white noise processes. It is shown that every Gaussian colored noise can be expressed as the output of a set of linear fractional stochastic differential equations whose solution is a weighted sum of fractional Brownian motions. The exact form of the weighting coefficients is given and it is shown that it is related to the fractional moments of the target spectral density of the colored noise.

FOS: Computer and information sciencesStatistics and ProbabilityDifferential equationFOS: Physical sciencesGeneral Physics and AstronomyStatistics - ComputationStochastic differential equationsymbols.namesakeSpectral MomentsApplied mathematicsStationary processeGaussian processCondensed Matter - Statistical MechanicsComputation (stat.CO)Mathematical PhysicsMathematicsGeneralized functionStatistical Mechanics (cond-mat.stat-mech)Statistical and Nonlinear PhysicsMathematical Physics (math-ph)White noiseClosed and exact differential formsColors of noiseGaussian noiseFractional CalculuModeling and SimulationsymbolsSettore ICAR/08 - Scienza Delle Costruzioni
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Surrogate outcomes and transportability

2019

Identification of causal effects is one of the most fundamental tasks of causal inference. We consider an identifiability problem where some experimental and observational data are available but neither data alone is sufficient for the identification of the causal effect of interest. Instead of the outcome of interest, surrogate outcomes are measured in the experiments. This problem is a generalization of identifiability using surrogate experiments and we label it as surrogate outcome identifiability. We show that the concept of transportability provides a sufficient criteria for determining surrogate outcome identifiability for a large class of queries.

FOS: Computer and information scienceskokeilucausalityGeneralizationComputer scienceComputer Science - Artificial Intelligence02 engineering and technologyMachine learningcomputer.software_genreOutcome (game theory)Theoretical Computer ScienceMethodology (stat.ME)do-calculusArtificial Intelligence020204 information systemsalgoritmit0202 electrical engineering electronic engineering information engineeringStatistics - Methodologyta113päättelyta112experimentbusiness.industrySurrogate endpointverkkoteoriaApplied MathematicsCausal effectta111graphidentifiabilityIdentification (information)Artificial Intelligence (cs.AI)Causal inferencekausaliteettiIdentifiability020201 artificial intelligence & image processingObservational studyArtificial intelligencebusinessmediatorcomputerSoftware
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On differences and similarities in the analysis of Lorenz, Chen, and Lu systems

2015

Currently it is being actively discussed the question of the equivalence of various Lorenz-like systems and the possibility of universal consideration of their behavior (Algaba et al., 2013a,b, 2014b,c; Chen, 2013; Chen and Yang, 2013; Leonov, 2013a), in view of the possibility of reduction of such systems to the same form with the help of various transformations. In the present paper the differences and similarities in the analysis of the Lorenz, the Chen and the Lu systems are discussed. It is shown that the Chen and the Lu systems stimulate the development of new methods for the analysis of chaotic systems. Open problems are discussed.

FOS: Physical sciencesLyapunov exponentLorenz-like systemsLu systemChaotic analog of 16th Hilbert problemReduction (complexity)symbols.namesakeChenDevelopment (topology)Lorenz systemChaotic systemsCalculusApplied mathematicsEquivalence (measure theory)MathematicsbiologyApplied Mathematicsta111Lorenz systembiology.organism_classificationNonlinear Sciences - Chaotic DynamicsComputational MathematicsChen systemsymbolsChaotic Dynamics (nlin.CD)Lyapunov exponentApplied Mathematics and Computation
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Dynamic Finite Element analysis of fractionally damped structural systems in the time domain

2015

Visco-elastic material models with fractional characteristics have been used for several decades. This paper provides a simple methodology for Finite-Element-based dynamic analysis of structural systems with viscosity characterized by fractional derivatives of the strains. In particular, a re-formulation of the well-known Newmark method taking into account fractional derivatives discretized via the Grunwald–Letnikov summation allows the analysis of structural systems using standard Finite Element technology.

Finite element methodDiscretizationMechanical EngineeringMathematical analysisStructural systemStructural analysiComputational MechanicsCalculationViscoelasticityFinite element methodViscoelasticityFractional calculusStrainSimple (abstract algebra)Newmark-beta methodTime domainMathematics
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Finite element method on fractional visco-elastic frames

2016

Viscoelastic behavior is defined by fractional operators.Quasi static FEM analysis of frames with fractional constitutive law is performed.FEM solution is decoupled into a set of fractional Kelvin Voigt elements.Proposed approach could be easily integrated in existing FEM codes. In this study the Finite Element Method (FEM) on viscoelastic frames is presented. It is assumed that the Creep function of the constituent material is of power law type, as a consequence the local constitutive law is ruled by fractional operators. The Euler Bernoulli beam and the FEM for the frames are introduced. It is shown that the whole system is ruled by a set of coupled fractional differential equations. In q…

Finite element methodMechanical EngineeringConstitutive equationMathematical analysis02 engineering and technologyFunction (mathematics)Type (model theory)021001 nanoscience & nanotechnologyFractional calculuPower lawViscoelasticityFinite element methodComputer Science ApplicationsFractional calculus020303 mechanical engineering & transports0203 mechanical engineeringModeling and SimulationFractional viscoelasticityGeneral Materials Science0210 nano-technologySettore ICAR/08 - Scienza Delle CostruzioniQuasistatic processCaputo's fractional derivativeCivil and Structural EngineeringMathematics
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On minimal non-PC-groups

2009

On dit qu'un groupe G est un PC-groupe, si pour tout x ∈ G, G/C G (x G ) est une extension d'un groupe polycyclique par un groupe fini. Un non-PC-groupe minimal est un groupe qui n'est pas un PC-groupe mais dont tous les sous-groupes propres sont des PC-groupes. Notre principal resultat est qu'un non-PC-groupe minimal ayant un groupe quotient fini non-trivial est une extension cyclique finie d'un groupe abelien divisible de rang fini.

Finite groupAlgebra and Number Theory$PC$-groupApplied MathematicsCyclic groupCombinatoricsSettore MAT/02 - Algebraminimal non-$PC$ groupsubgroups of finite indexpolycyclic-by-finite groupCalculusRank (graph theory)Geometry and TopologySettore MAT/03 - GeometriaAbelian groupAnalysisMathematics
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Repetition times for Gibbsian sources

1999

In this paper we consider the class of stochastic stationary sources induced by one-dimensional Gibbs states, with Holder continuous potentials. We show that the time elapsed before the source repeats its first n symbols, when suitably renormalized, converges in law either to a log-normal distribution or to a finite mixture of exponential random variables. In the first case we also prove a large deviation result.

Finite mixtureClass (set theory)Repetition (rhetorical device)Applied MathematicsPROCESSOS ESTOCÁSTICOSGeneral Physics and AstronomyHölder conditionStatistical and Nonlinear PhysicsExponential functionDistribution (mathematics)CalculusStatistical physicsRandom variableMathematical PhysicsMathematics
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