Search results for "Variables"

showing 10 items of 578 documents

A Unified Approach to Likelihood Inference on Stochastic Orderings in a Nonparametric Context

1998

Abstract For data in a two-way contingency table with ordered margins, we consider various hypotheses of stochastic orders among the conditional distributions considered by rows and show that each is equivalent to requiring that an invertible transformation of the vectors of conditional row probabilities satisfies an appropriate set of linear inequalities. This leads to the construction of a general algorithm for maximum likelihood estimation under multinomial sampling and provides a simple framework for deriving the asymptotic distribution of log-likelihood ratio tests. The usual stochastic ordering and the so called uniform and likelihood ratio orderings are considered as special cases. I…

Statistics and ProbabilityCombinatoricsIndependent and identically distributed random variablesLinear inequalityTransformation (function)Likelihood-ratio testAsymptotic distributionApplied mathematicsConditional probability distributionStatistics Probability and UncertaintyStochastic orderingStatistical hypothesis testingMathematicsJournal of the American Statistical Association
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Stochastic order characterization of uniform integrability and tightness

2013

We show that a family of random variables is uniformly integrable if and only if it is stochastically bounded in the increasing convex order by an integrable random variable. This result is complemented by proving analogous statements for the strong stochastic order and for power-integrable dominating random variables. Especially, we show that whenever a family of random variables is stochastically bounded by a p-integrable random variable for some p>1, there is no distinction between the strong order and the increasing convex order. These results also yield new characterizations of relative compactness in Wasserstein and Prohorov metrics.

Statistics and ProbabilityDiscrete mathematicsPure mathematicsRandom fieldMultivariate random variableProbability (math.PR)ta111Random functionRandom element60E15 60B10 60F25Stochastic orderingFunctional Analysis (math.FA)Mathematics - Functional AnalysisRandom variateConvergence of random variablesStochastic simulationFOS: MathematicsStatistics Probability and UncertaintyMathematics - ProbabilityMathematicsStatistics & Probability Letters
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Uniform measure density condition and game regularity for tug-of-war games

2018

We show that a uniform measure density condition implies game regularity for all 2 < p < ∞ in a stochastic game called “tug-of-war with noise”. The proof utilizes suitable choices of strategies combined with estimates for the associated stopping times and density estimates for the sum of independent and identically distributed random vectors. peerReviewed

Statistics and ProbabilityIndependent and identically distributed random variablesComputer Science::Computer Science and Game Theorygame regularitydensity estimate for the sum of i.i.d. random vectorsTug of war01 natural sciencesMeasure (mathematics)$p$-regularityMathematics - Analysis of PDEsFOS: MathematicsApplied mathematicspeliteoriastochastic games0101 mathematics91A15 60G50 35J92Mathematicsp-harmonic functionsstokastiset prosessit$p$-harmonic functionsosittaisdifferentiaaliyhtälöthitting probability010102 general mathematicsStochastic gametug-of-war gamesProbability (math.PR)uniform measure density condition010101 applied mathematicsNoiseuniform distribution in a ballMathematics - ProbabilityAnalysis of PDEs (math.AP)
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Recursive estimation of the conditional geometric median in Hilbert spaces

2012

International audience; A recursive estimator of the conditional geometric median in Hilbert spaces is studied. It is based on a stochastic gradient algorithm whose aim is to minimize a weighted L1 criterion and is consequently well adapted for robust online estimation. The weights are controlled by a kernel function and an associated bandwidth. Almost sure convergence and L2 rates of convergence are proved under general conditions on the conditional distribution as well as the sequence of descent steps of the algorithm and the sequence of bandwidths. Asymptotic normality is also proved for the averaged version of the algorithm with an optimal rate of convergence. A simulation study confirm…

Statistics and ProbabilityMallows-Wasserstein distanceRobbins-Monroasymptotic normalityCLTcentral limit theoremAsymptotic distributionMathematics - Statistics TheoryStatistics Theory (math.ST)01 natural sciencesMallows–Wasserstein distanceonline data010104 statistics & probability[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]60F05FOS: MathematicsApplied mathematics[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematics62L20MathematicsaveragingSequential estimation010102 general mathematicsEstimatorRobbins–MonroConditional probability distribution[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Geometric medianstochastic gradient[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]robust estimatorRate of convergenceConvergence of random variablesStochastic gradient.kernel regressionsequential estimationKernel regressionStatistics Probability and Uncertainty
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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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Influence functions and efficiencies of the canonical correlation and vector estimates based on scatter and shape matrices

2006

In this paper, the influence functions and limiting distributions of the canonical correlations and coefficients based on affine equivariant scatter matrices are developed for elliptically symmetric distributions. General formulas for limiting variances and covariances of the canonical correlations and canonical vectors based on scatter matrices are obtained. Also the use of the so-called shape matrices in canonical analysis is investigated. The scatter and shape matrices based on the affine equivariant Sign Covariance Matrix as well as the Tyler's shape matrix serve as examples. Their finite sample and limiting efficiencies are compared to those of the Minimum Covariance Determinant estima…

Statistics and ProbabilityNumerical AnalysisSign covariance matrixKanoniset korrelaatiot ja vektoritCovariance matrixMathematical analysisTyler's estimateShape matrixCanonical vectorsCovarianceCanonical correlationsCanonical analysisMatrix (mathematics)Canonical variablesCalculusSymmetric matrixEquivariant mapAffine transformationStatistics Probability and UncertaintyCanonical correlationMathematicsJournal of Multivariate Analysis
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On (n-l)-wise and joint independence and normality of n Random variables: an example

1981

An example is given of a vector of n random variables such that any (n-1)-dimensional subvector consists of n-1 independent standard normal variables. The whole vector however is neither independent nor normal.

Statistics and ProbabilityPairwise independenceCombinatoricsExchangeable random variablesIndependent and identically distributed random variablesStandard normal deviateMultivariate random variableSum of normally distributed random variablesStatisticsMarginal distributionCentral limit theoremMathematicsCommunications in Statistics - Theory and Methods
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On the empirical spectral distribution for certain models related to sample covariance matrices with different correlations

2021

Given [Formula: see text], we study two classes of large random matrices of the form [Formula: see text] where for every [Formula: see text], [Formula: see text] are iid copies of a random variable [Formula: see text], [Formula: see text], [Formula: see text] are two (not necessarily independent) sets of independent random vectors having different covariance matrices and generating well concentrated bilinear forms. We consider two main asymptotic regimes as [Formula: see text]: a standard one, where [Formula: see text], and a slightly modified one, where [Formula: see text] and [Formula: see text] while [Formula: see text] for some [Formula: see text]. Assuming that vectors [Formula: see t…

Statistics and ProbabilityPhysicsAlgebra and Number TheorySpectral power distributionComputer Science::Information RetrievalProbability (math.PR)Astrophysics::Instrumentation and Methods for AstrophysicsBlock (permutation group theory)Marchenko–Pastur lawComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Bilinear form60F05 60B20 47N30Sample mean and sample covarianceCombinatoricsConvergence of random variablesFOS: Mathematicssample covariance matricesComputer Science::General LiteratureDiscrete Mathematics and CombinatoricsRandom matriceshigh dimensional statisticsStatistics Probability and UncertaintyRandom matrixRandom variableMathematics - ProbabilityRandom Matrices: Theory and Applications
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Complete spectrum and scalar products for the open spin-1/2 XXZ quantum chains with non-diagonal boundary terms

2013

We use the quantum separation of variable (SOV) method to construct the eigenstates of the open XXZ chain with the most general boundary terms. The eigenstates in the inhomogeneous case are constructed in terms of solutions of a system of quadratic equations. This SOV representation permits us to compute scalar products and can be used to calculate form factors and correlation functions.

Statistics and ProbabilityPhysicsHigh Energy Physics - TheoryStatistical Mechanics (cond-mat.stat-mech)Nonlinear Sciences - Exactly Solvable and Integrable Systems010308 nuclear & particles physicsDiagonalScalar (mathematics)Separation of variablesFOS: Physical sciencesStatistical and Nonlinear PhysicsMathematical Physics (math-ph)01 natural sciencesQuadratic equationNonlinear Sciences::Exactly Solvable and Integrable SystemsHigh Energy Physics - Theory (hep-th)0103 physical sciencesExactly Solvable and Integrable Systems (nlin.SI)Statistics Probability and Uncertainty010306 general physicsQuantumEigenvalues and eigenvectorsMathematical PhysicsCondensed Matter - Statistical MechanicsMathematical physics
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Open spin chains with generic integrable boundaries: Baxter equation and Bethe ansatz completeness from separation of variables

2014

28 pages; International audience; We solve the longstanding problem to define a functional characterization of the spectrum of the transfer matrix associated to the most general spin-1/2 representations of the 6-vertex reflection algebra for general inhomogeneous chains. The corresponding homogeneous limit reproduces the spectrum of the Hamiltonian of the spin-1/2 open XXZ and XXX quantum chains with the most general integrable boundaries. The spectrum is characterized by a second order finite difference functional equation of Baxter type with an inhomogeneous term which vanishes only for some special but yet interesting non-diagonal boundary conditions. This functional equation is shown to…

Statistics and ProbabilityPhysicsIntegrable system010308 nuclear & particles physics[PHYS.HTHE]Physics [physics]/High Energy Physics - Theory [hep-th][PHYS.MPHY]Physics [physics]/Mathematical Physics [math-ph]Finite differenceSeparation of variablesStatistical and Nonlinear Physics01 natural sciencesTransfer matrixBethe ansatzsymbols.namesake0103 physical sciencessymbols[NLIN.NLIN-SI]Nonlinear Sciences [physics]/Exactly Solvable and Integrable Systems [nlin.SI]Boundary value problemStatistics Probability and Uncertainty010306 general physicsHamiltonian (quantum mechanics)QuantumMathematical physics
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