Search results for "Probability Distribution"

showing 10 items of 263 documents

Explicit Upper Bound for Entropy Numbers

2004

We give an explicit upper bound for the entropy numbers of the embedding I : W r,p(Ql) → C(Ql) where Ql = (−l, l)m ⊂ Rm, r ∈ N, p ∈ (1,∞) and rp > m.

CombinatoricsApplied MathematicsMaximum entropy probability distributionEmbeddingEntropy (information theory)Min entropyUpper and lower boundsAnalysisEntropy rateQuantum relative entropyJoint quantum entropyMathematicsZeitschrift für Analysis und ihre Anwendungen
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Testing for selectivity in the dependence of random variables on external factors

2008

Random variables AA and BB, whose joint distribution depends on factors (x,y)(x,y), are selectively influenced by xx and yy, respectively, if AA and BB can be represented as functions of, respectively, (x,SA,C)(x,SA,C) and (y,SB,C)(y,SB,C), where SA,SB,CSA,SB,C are stochastically independent and do not depend on (x,y)(x,y). Selective influence implies selective dependence of marginal distributions on the respective factors: thus no parameter of AA may depend on yy. But parameters characterizing stochastic interdependence of AA and BB, such as their mixed moments, are generally functions of both xx and yy. We derive two simple necessary conditions for selective dependence of (A,B)(A,B) on (x…

CombinatoricsCrystallographyJoint probability distributionApplied MathematicsSelectivityRandom variableGeneral PsychologyMathematicsJournal of Mathematical Psychology
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Entropy, transverse entropy and partitions of unity

1994

AbstractThe topological entropy of a transformation is expressed in terms of partitions of unity. The transverse entropy of a flow tangential to a foliation is defined and expresed in a similar way. The geometric entropy of a foliation of a Riemannian manifold is compared with the transverse entropy of its geodesic flow.

CombinatoricsTransverse planeEntropy (classical thermodynamics)Applied MathematicsGeneral MathematicsConfiguration entropyMaximum entropy probability distributionMathematics::Differential GeometryStatistical physicsJoint quantum entropyMathematicsErgodic Theory and Dynamical Systems
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Pragmatic languages with universal grammars

2012

Abstract This paper constructs the equilibrium for a specific code that can be seen as a “universal grammar” in a class of common interest Sender–Receiver games where players communicate through a noisy channel. We propose a Senderʼs signaling strategy which does not depend on either the game payoffs or the initial probability distribution. The Receiverʼs strategy partitions the set of possible sequences into subsets, with a single action assignment to each of them. The Senderʼs signaling strategy is a Nash equilibrium, i.e. when the Receiver responds best to the Senderʼs strategy, the Sender has no incentive to deviate. An example shows that a tie-breaking decoding is crucial for the block…

Computer Science::Computer Science and Game TheoryEconomics and EconometricsTheoretical computer sciencejel:C61jel:D82Symmetric gamejel:C73TheoryofComputation_GENERALgrammar pragmatic language prototypes separating equilibriasymbols.namesakeNash equilibriumsymbolsCode (cryptography)Probability distributionCommunication sourceSignaling gameSet (psychology)FinanceDecoding methodsComputer Science::Information TheoryMathematicsGames and Economic Behavior
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Ranking-Oriented Collaborative Filtering: A Listwise Approach

2016

Collaborative filtering (CF) is one of the most effective techniques in recommender systems, which can be either rating oriented or ranking oriented. Ranking-oriented CF algorithms demonstrated significant performance gains in terms of ranking accuracy, being able to estimate a precise preference ranking of items for each user rather than the absolute ratings (as rating-oriented CF algorithms do). Conventional memory-based ranking-oriented CF can be referred to as pairwise algorithms. They represent each user as a set of preferences on each pair of items for similarity calculations and predictions. In this study, we propose ListCF, a novel listwise CF paradigm that seeks improvement in bot…

Computer science02 engineering and technologyRecommender systemcomputer.software_genreMachine learningSet (abstract data type)020204 information systems0202 electrical engineering electronic engineering information engineeringCollaborative filteringDivergence (statistics)ranking-oriented collaborative filteringta113business.industryGeneral Business Management and AccountingComputer Science ApplicationsRankingcollaborative filteringBenchmark (computing)Probability distribution020201 artificial intelligence & image processingPairwise comparisonArtificial intelligenceData miningrecommender systemsbusinesscomputerInformation SystemsACM Transactions on Information Systems
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Adaptive Importance Sampling: The past, the present, and the future

2017

A fundamental problem in signal processing is the estimation of unknown parameters or functions from noisy observations. Important examples include localization of objects in wireless sensor networks [1] and the Internet of Things [2]; multiple source reconstruction from electroencephalograms [3]; estimation of power spectral density for speech enhancement [4]; or inference in genomic signal processing [5]. Within the Bayesian signal processing framework, these problems are addressed by constructing posterior probability distributions of the unknowns. The posteriors combine optimally all of the information about the unknowns in the observations with the information that is present in their …

Computer scienceBayesian probabilityPosterior probabilityInference02 engineering and technologyMachine learningcomputer.software_genre01 natural sciences010104 statistics & probabilityMultidimensional signal processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingPrior probability0202 electrical engineering electronic engineering information engineering0101 mathematicsElectrical and Electronic EngineeringComputingMilieux_MISCELLANEOUSbusiness.industryApplied Mathematics020206 networking & telecommunicationsApproximate inferenceSignal ProcessingProbability distributionArtificial intelligencebusinessAlgorithmcomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingImportance sampling
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A New Simple Computational Method of Simultaneous Constructing and Comparing Confidence Intervals of Shortest Length and Equal Tails for Making Effic…

2021

A confidence interval is a range of values that provides the user with useful information about how accurately a statistic estimates a parameter. In the present paper, a new simple computational method is proposed for simultaneous constructing and comparing confidence intervals of shortest length and equal tails in order to make efficient decisions under parametric uncertainty. This unified computational method provides intervals in several situations that previously required separate analysis using more advanced methods and tables for numerical solutions. In contrast to the Bayesian approach, the proposed approach does not depend on the choice of priors and is a novelty in the theory of st…

Computer scienceBayesian probabilityPrior probabilityProbability distributionQuantile functionPivotal quantityAlgorithmConfidence intervalParametric statisticsQuantile
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Applicability of the Poisson distribution to model the data of the German Children's Cancer Registry.

1995

Since 1980 the German Children's Cancer Registry has documented all childhood malignancies in the Federal Republic of Germany. Various statistical procedures have been proposed to identify municipalities or other geographic units with increased numbers of malignancies. Usually the Poisson distribution, which requires the malignancies to be distributed homogeneously and uncorrelated, is applied. Other discrete statistical distributions (so-called cluster distributions) like the generalized or compound Poisson distributions are applicable more generally. In this paper we present a first explorative approach to the question of whether it is necessary to use one of these cluster distributions t…

Computer scienceBiophysicsPoisson distributionDisease clusterGermansymbols.namesakeGermanyNeoplasmsStatisticsEconometricsHumansPoisson DistributionRegistriesChildGeneral Environmental ScienceProbabilityRadiationModels StatisticalGermany WestFederal republic of germanylanguage.human_languageUncorrelatedCancer registrysymbolslanguageProbability distributionRadiation and environmental biophysics
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A Bayesian unified framework for risk estimation and cluster identification in small area health data analysis.

2020

Many statistical models have been proposed to analyse small area disease data with the aim of describing spatial variation in disease risk. In this paper, we propose a Bayesian hierarchical model that simultaneously allows for risk estimation and cluster identification. Our model formulation assumes that there is an unknown number of risk classes and small areas are assigned to a risk class by means of independent allocation variables. Therefore, areas within each cluster are assumed to share a common risk but they may be geographically separated. The posterior distribution of the parameter representing the number of risk classes is estimated using a novel procedure that combines its prior …

Computer scienceEpidemiologyPathology and Laboratory Medicine01 natural sciencesGeographical locations010104 statistics & probabilityChickenpoxMathematical and Statistical TechniquesStatisticsMedicine and Health SciencesPublic and Occupational Health0303 health sciencesMultidisciplinarySimulation and ModelingQREuropeIdentification (information)Medical MicrobiologySmall-Area AnalysisViral PathogensVirusesPhysical SciencesMedicinePathogensAlgorithmsResearch ArticleHerpesvirusesScienceBayesian probabilityPosterior probabilityBayesian MethodDisease SurveillanceDisease clusterResearch and Analysis MethodsRisk AssessmentMicrobiologyVaricella Zoster Virus03 medical and health sciencesRisk classPrior probabilityCovariateBayesian hierarchical modelingHumansEuropean Union0101 mathematicsMicrobial Pathogens030304 developmental biologyBiology and life sciencesOrganismsStatistical modelBayes TheoremProbability TheoryProbability DistributionMarginal likelihoodConvolutionSpainPeople and placesDNA virusesMathematical FunctionsMathematicsPloS one
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Error mitigation using RaptorQ codes in an experimental indoor free space optical link under the influence of turbulence

2015

In free space optical (FSO) communications, several factors can strongly affect the link quality. Among them, one of the most important impairments that can degrade the FSO link quality and its reliability even under the clear sky conditions consists of optical turbulence. In this work, the authors investigate the generation of both weak and moderate turbulence regimes in an indoor environment to assess the FSO link quality. In particular, they show that, due to the presence of the turbulence, the link experiences both erasure errors and packet losses during transmission, and also compare the experimental statistical distribution of samples with the predicted Gamma Gamma model. Furthermore,…

Computer scienceOptical linkReliability (computer networking)Optical linksTelecommunication network reliabilityRytov variance valueSettore ING-INF/01 - ElettronicaTelecomunicacióRaptorQ codesRedundancy (information theory)Indoor free space optical linkFSO communicationsStatisticsTEORIA DE LA SEÑAL Y COMUNICACIONESRedundancy (engineering)Gamma Gamma modelrateless codeElectrical and Electronic Engineeringpacket error rate (PER)Error-free transmissionNetwork packetbusiness.industrySettore ING-INF/03 - TelecomunicazioniSettore ING-INF/02 - Campi ElettromagneticiÒpticaComputer Science ApplicationsTransmission (telecommunications)Bit error rateErasureProbability distributionFree Space Optical (FSO) communicationTelecommunicationsbusinessOptical turbulenceFSO link reliabilityindoor linkError mitigation
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