Search results for "MOMENTS"

showing 10 items of 151 documents

Statistical correlation of fractional oscillator response by complex spectral moments and state variable expansion

2016

Abstract The statistical characterization of the oscillator response with non-integer order damping under Gaussian noise represents an important challenge in the modern stochastic mechanics. In fact, this kind of problem appears in several issues of different type (wave propagation in viscoelastic media, Brownian motion, fluid dynamics, RLC circuit, etc.). The aim of this paper is to provide a stochastic characterization of the stationary response of linear fractional oscillator forced by normal white noise. In particular, this paper shows a new method to obtain the correlation function by exact complex spectral moments. These complex quantities contain all the information to describe the r…

State variableNon-Newtonian damping Fractional-order state variables Analytical stationary variance Exact complex spectral moments02 engineering and technologyFractional-order state variable01 natural sciencesAnalytical stationary variance010305 fluids & plasmassymbols.namesake0203 mechanical engineering0103 physical sciencesExact complex spectral momentNumerical AnalysiBrownian motionMathematicsNumerical AnalysisMellin transformStochastic processApplied MathematicsMathematical analysisWhite noiseNon-Newtonian dampingMoment (mathematics)Correlation function (statistical mechanics)020303 mechanical engineering & transportsGaussian noiseModeling and Simulationsymbols
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Olley–Pakes productivity decomposition: computation and inference

2016

Summary We show how a moment-based estimation procedure can be used to compute point estimates and standard errors for the two components of the widely used Olley–Pakes decomposition of aggregate (weighted average) productivity. When applied to business level microdata, the procedure allows for autocovariance and heteroscedasticity robust inference and hypothesis testing about, for example, the coevolution of the productivity components in different groups of firms. We provide an application to Finnish firm level data and find that formal statistical inference casts doubt on the conclusions that one might draw on the basis of a visual inspection of the components of the decomposition.

Statistics and ProbabilityEconomics and EconometricsHeteroscedasticityproductivitytuottavuusInferenceFrequentist inference0502 economics and businessStatisticsStatistical inferenceEconometricsPoint estimation050207 economics050205 econometrics MathematicsStatistical hypothesis testingpäättelyta112inferenceta51105 social sciencesgeneralized method of momentsAutocovarianceweighted averageFiducial inferenceStatistics Probability and UncertaintySocial Sciences (miscellaneous)Journal of the Royal Statistical Society Series A: Statistics in Society
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Probabilistic characterization of nonlinear systems under α-stable white noise via complex fractional moments

2015

Abstract The probability density function of the response of a nonlinear system under external α -stable Levy white noise is ruled by the so called Fractional Fokker–Planck equation. In such equation the diffusive term is the Riesz fractional derivative of the probability density function of the response. The paper deals with the solution of such equation by using the complex fractional moments. The analysis is performed in terms of probability density for a linear and a non-linear half oscillator forced by Levy white noise with different stability indexes α . Numerical results are reported for a wide range of non-linearity of the mechanical system and stability index of the Levy white nois…

Statistics and ProbabilityFractional Fokker-Planck equationα-stable white noiseMathematical analysisProbabilistic logicStatistical and Nonlinear PhysicsProbability density functionCondensed Matter PhysicWhite noiseComplex fractional momentStability (probability)Fractional calculusMechanical systemNonlinear systemNonlinear systemRange (statistics)Complex fractional moments; Fractional Fokker-Planck equation; Nonlinear systems; α-stable white noise; Condensed Matter Physics; Statistics and ProbabilityMathematicsPhysica A: Statistical Mechanics and its Applications
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Posterior moments and quantiles for the normal location model with Laplace prior

2021

We derive explicit expressions for arbitrary moments and quantiles of the posterior distribution of the location parameter η in the normal location model with Laplace prior, and use the results to approximate the posterior distribution of sums of independent copies of η.

Statistics and ProbabilityLaplace priorsLaplace priorLocation parameterreflected generalized gamma priorSettore SECS-P/05Posterior probability0211 other engineering and technologiesSettore SECS-P/05 - Econometria02 engineering and technology01 natural sciencesCornish-Fisher approximation010104 statistics & probabilityStatistics::Methodologyposterior quantile0101 mathematicsposterior moments and cumulantsMathematicsreflected generalized gamma priors021103 operations researchLaplace transformLocation modelMathematical analysisStatistics::Computationposterior moments and cumulantCornish–Fisher approximationSettore SECS-S/01 - StatisticaNormal location modelposterior quantilesQuantileCommunications in Statistics - Theory and Methods
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Fractional calculus approach to the statistical characterization of random variables and vectors

2009

Fractional moments have been investigated by many authors to represent the density of univariate and bivariate random variables in different contexts. Fractional moments are indeed important when the density of the random variable has inverse power-law tails and, consequently, it lacks integer order moments. In this paper, starting from the Mellin transform of the characteristic function and by fractional calculus method we present a new perspective on the statistics of random variables. Introducing the class of complex moments, that include both integer and fractional moments, we show that every random variable can be represented within this approach, even if its integer moments diverge. A…

Statistics and ProbabilityMellin transformStatistical Mechanics (cond-mat.stat-mech)Characteristic function (probability theory)Multivariate distributionMultivariate random variableMathematical analysisFOS: Physical sciencesMoment-generating functionCondensed Matter PhysicsFractional calculusFractional and complex moments; Multivariate distributions; Power-law tails; Inverse Mellin transformFractional and complex momentIngenieurwissenschaftenApplied mathematicsddc:620Inverse Mellin transformSettore ICAR/08 - Scienza Delle CostruzioniRandom variableCondensed Matter - Statistical MechanicsMathematicsInteger (computer science)Taylor expansions for the moments of functions of random variablesPower-law tail
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Einstein-Smoluchowsky equation handled by complex fractional moments

2014

In this paper the response of a non linear half oscillator driven by α-stable white noise in terms of probability density function (PDF) is investigated. The evolution of the PDF of such a system is ruled by the so called Einstein-Smoluchowsky equation involving, in the diffusive term, the Riesz fractional derivative. The solution is obtained by the use of complex fractional moments of the PDF, calculated with the aid of Mellin transform operator. It is shown that solution can be found for various values of stability index α and for any nonlinear function of the drift term in the stochastic differential equation.

Stochastic partial differential equationNonlinear systemStochastic differential equationMellin transformDifferential equationOperator (physics)Mathematical analysisProbability density functiona-stable white noise Nonlinear systems Einstein-Smoluchowsky equation Complex fractional momentsFractional calculusMathematics
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Combined dynamic response of primary and multiply connected cascaded secondary subsystems

1991

A method is proposed for the deterministic and stochastic non-stationary analysis of linear composite systems with cascaded secondary subsystems subjected to a seismic input. This method makes it possible to evaluate, by means of a unitary formulation, the deterministic and non-stationary stochastic response of both classically and non-classically damped subsystems and of secondary subsystems multiply supported on the primary one, as well as the ground. The proposed procedure is very efficient from a computational point of view, because of the Kronecker algebra systematically employed. Indeed, by using this algebra, it is possible to obtain in a very compact and elegant form the eigenproper…

Stochastic processFunction (mathematics)Geotechnical Engineering and Engineering GeologyTopologyUnitary stateSecond order momentssymbols.namesakeSimple (abstract algebra)Ordinary differential equationKronecker deltaEarth and Planetary Sciences (miscellaneous)symbolsPoint (geometry)AlgorithmMathematicsEarthquake Engineering & Structural Dynamics
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REGIONAL FREQUENCY ANALYSIS FOR EXTREME RAINFALL IN SICILY

2008

TCEVMGsEXTREME RAINFALLL-MOMENTS
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Analisi regionale delle piogge intense in Sicilia

2008

TCEVPIOGGE INTENSEREGIONALIZZAZIONEL-MOMENTS
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Ultimate Order Statistics-Based Prototype Reduction Schemes

2013

Published version of a chapter in the book: AI 2013: Advances in Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-319-03680-9_42 The objective of Prototype Reduction Schemes (PRSs) and Border Identification (BI) algorithms is to reduce the number of training vectors, while simultaneously attempting to guarantee that the classifier built on the reduced design set performs as well, or nearly as well, as the classifier built on the original design set. In this paper, we shall push the limit on the field of PRSs to see if we can obtain a classification accuracy comparable to the optimal, by condensing the information in the data set into a single tr…

Training setComputer scienceVDP::Mathematics and natural science: 400::Information and communication science: 420::Algorithms and computability theory: 422Order statisticcomputer.software_genreSupport vector machineData setBayes' theoremclassification using Order Statistics (OS)CMOSPrototype Reduction SchemesData miningmoments of OSClassifier (UML)computerParametric statistics
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