Search results for "Random Variables"

showing 7 items of 37 documents

Variable Length Memory Chains: Characterization of stationary probability measures

2021

Variable Length Memory Chains (VLMC), which are generalizations of finite order Markov chains, turn out to be an essential tool to modelize random sequences in many domains, as well as an interesting object in contemporary probability theory. The question of the existence of stationary probability measures leads us to introduce a key combinatorial structure for words produced by a VLMC: the Longest Internal Suffix. This notion allows us to state a necessary and sufficient condition for a general VLMC to admit a unique invariant probability measure. This condition turns out to get a much simpler form for a subclass of VLMC: the stable VLMC. This natural subclass, unlike the general case, enj…

Statistics and ProbabilityPure mathematicsLongest Internal SuffixStationary distributionMarkov chain60J05 60C05 60G10Probability (math.PR)010102 general mathematics01 natural sciencesMeasure (mathematics)Variable Length Memory Chains010104 statistics & probabilityProbability theoryConvergence of random variablesFOS: MathematicsCountable setState spaceRenewal theory[MATH]Mathematics [math]0101 mathematicsstable context treessemi-Markov chainsMathematics - Probabilitystationary probability measureMathematicsBernoulli
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On almost sure convergence of amarts and martingales without the Radon-Nikodym property

1988

It is shown here that for any Banach spaceE-valued amart (X n) of classB, almost sure convergence off(Xn) tof(X) for eachf in a total subset ofE * implies scalar convergence toX.

Statistics and ProbabilityRadon–Nikodym theoremDiscrete mathematicsPure mathematicsConvergence of random variablesGeneral MathematicsScalar (mathematics)Statistics Probability and UncertaintyMathematicsJournal of Theoretical Probability
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Level-crossing rate and average duration of fades of the envelope of mobile-to-mobile fading channels in K-parallel dual-hop relay networks

2009

©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE." Article also available from publisher: http://dx.doi.org/10.1109/WCSP.2009.5371574 This paper studies the fading behavior of narrowband mobile-to-mobile (M2M) fading channels in dual-hop distributed cooperative multi-relay systems under non-line-of-sight (NLOS) propagation conditions. M2M fading channels considered here are associated with amplify-and-forward …

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Independent and identically distributed random variablesComputer sciencebusiness.industryComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSData_CODINGANDINFORMATIONTHEORYTopologylaw.inventionFading distributionNarrowbandRelaylawMobile stationVDP::Technology: 500::Information and communication technology: 550::Telecommunication: 552Computer Science::Networking and Internet ArchitectureCommunications satelliteFadingTelecommunicationsbusinessComputer Science::Information TheoryRayleigh fadingCommunication channel2009 International Conference on Wireless Communications & Signal Processing
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Comment on "Estimating average annual per cent change in trend analysis"

2010

We discuss some issues relevant to paper of Clegg and co-authors published in Statistics in Medicine; 28, 3670-3682. Emphasis is on computation of the variance of the sum of products of two estimates, slopes and breakpoints.

break-pointtrend analysiproduct of random variablessegmented regressionSettore SECS-S/01 - Statistica
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All-Possible-Couplings Approach to Measuring Probabilistic Context.

2013

From behavioral sciences to biology to quantum mechanics, one encounters situations where (i) a system outputs several random variables in response to several inputs, (ii) for each of these responses only some of the inputs may "directly" influence them, but (iii) other inputs provide a "context" for this response by influencing its probabilistic relations to other responses. These contextual influences are very different, say, in classical kinetic theory and in the entanglement paradigm of quantum mechanics, which are traditionally interpreted as representing different forms of physical determinism. One can mathematically construct systems with other types of contextuality, whether or not …

lcsh:MedicineQuantum entanglementSocial and Behavioral Sciences01 natural sciencesQuantitative Biology - Quantitative MethodsJoint probability distributionPsychologyStatistical physicslcsh:ScienceQuantumQuantitative Methods (q-bio.QM)60B99 (Primary) 81Q99 91E45 (Secondary)PhysicsQuantum PhysicsMultidisciplinaryApplied MathematicsPhysics05 social sciencesComplex SystemsMental HealthMedicineMathematics - ProbabilityAlgorithmsResearch ArticleFOS: Physical sciencesContext (language use)Physical determinism050105 experimental psychologyProbability theory0103 physical sciencesFOS: Mathematics0501 psychology and cognitive sciences010306 general physicsQuantum MechanicsProbabilityta113BehaviorModels Statisticallcsh:RProbability (math.PR)Probabilistic logicRandom VariablesProbability TheoryKochen–Specker theoremFOS: Biological sciencesQuantum Theorylcsh:QQuantum EntanglementQuantum Physics (quant-ph)Mathematics
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The Joint Distribution Criterion and the Distance Tests for Selective Probabilistic Causality

2010

A general definition and a criterion (a necessary and sufficient condition) are formulated for an arbitrary set of external factors to selectively influence a corresponding set of random entities (generalized random variables, with values in arbitrary observation spaces), jointly distributed at every treatment (a set of factor values containing precisely one value of each factor). The random entities are selectively influenced by the corresponding factors if and only if the following condition, called the joint distribution criterion, is satisfied : there is a jointly distributed set of random entities, one entity for every value of every factor, such that every subset of this set that corr…

selective influenceComputer scienceGeneralizationlcsh:BF1-990Value (computer science)systems of random variablescomputer.software_genre050105 experimental psychologyCausality (physics)Set (abstract data type)03 medical and health sciences0302 clinical medicineJoint probability distributionHypothesis and TheoryPsychology0501 psychology and cognitive sciencesstochastically unrelatedGeneral PsychologyDiscrete mathematics05 social sciencesProbabilistic logicexternal factorsstochastic dependencejoint distributionlcsh:PsychologyProbabilistic causalitySum of normally distributed random variablesData miningcomputerRandom variable030217 neurology & neurosurgeryFrontiers in Psychology
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Context–content systems of random variables : The Contextuality-by-Default theory

2016

Abstract This paper provides a systematic yet accessible presentation of the Contextuality-by-Default theory. The consideration is confined to finite systems of categorical random variables, which allows us to focus on the basics of the theory without using full-scale measure-theoretic language. Contextuality-by-Default is a theory of random variables identified by their contents and their contexts, so that two variables have a joint distribution if and only if they share a context. Intuitively, the content of a random variable is the entity the random variable measures or responds to, while the context is formed by the conditions under which these measurements or responses are obtained. A …

ta113Theoretical computer scienceComputer scienceApplied Mathematicscouplings05 social sciencesta111Probabilistic logicContext (language use)01 natural sciencesMeasure (mathematics)050105 experimental psychologyconnectednessKochen–Specker theoremrandom variablesJoint probability distribution0103 physical sciences0501 psychology and cognitive sciencescontextualityNegative number010306 general physicsCategorical variableRandom variableGeneral PsychologyJournal of Mathematical Psychology
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