Search results for "Renewal process"

showing 8 items of 8 documents

Statistics of transitions for Markov chains with periodic forcing

2013

The influence of a time-periodic forcing on stochastic processes can essentially be emphasized in the large time behaviour of their paths. The statistics of transition in a simple Markov chain model permits to quantify this influence. In particular the first Floquet multiplier of the associated generating function can be explicitly computed and related to the equilibrium probability measure of an associated process in higher dimension. An application to the stochastic resonance is presented.

[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]Markov chain mixing timeMarkov kernelMarkov chainProbability (math.PR)Markov chainlarge time asymptoticStochastic matrixcentral limit theoremMarkov process[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]symbols.namesakeMarkov renewal processModeling and SimulationFloquet multipliersStatisticsFOS: MathematicssymbolsMarkov propertyExamples of Markov chainsstochastic resonance60J27 60F05 34C25[ MATH.MATH-PR ] Mathematics [math]/Probability [math.PR]Mathematics - ProbabilityMathematics
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ℓ1-Penalized Methods in High-Dimensional Gaussian Markov Random Fields

2016

In the last 20 years, we have witnessed the dramatic development of new data acquisition technologies allowing to collect massive amount of data with relatively low cost. is new feature leads Donoho to define the twenty-first century as the century of data. A major characteristic of this modern data set is that the number of measured variables is larger than the sample size; the word high-dimensional data analysis is referred to the statistical methods developed to make inference with this new kind of data. This chapter is devoted to the study of some of the most recent ℓ1-penalized methods proposed in the literature to make sparse inference in a Gaussian Markov random field (GMRF) defined …

Markov kernelMarkov random fieldMarkov chainComputer scienceStructured Graphical lassoVariable-order Markov model010103 numerical & computational mathematicsMarkov Random FieldMarkov model01 natural sciencesGaussian random field010104 statistics & probabilityHigh-Dimensional InferenceMarkov renewal processTuning Parameter SelectionMarkov propertyJoint Graphical lassoStatistical physics0101 mathematicsSettore SECS-S/01 - StatisticaGraphical lasso
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Strongly super-Poisson statistics replaced by a wide-pulse Poisson process: The billiard random generator

2021

Abstract In this paper we present a study on random processes consisting of delta pulses characterized by strongly super-Poisson statistics and calculate its spectral density. We suggest a method for replacing a strongly super-Poisson process with a wide-pulse Poisson process, while demonstrating that these two processes can be set in such a way to have similar spectral densities, the same mean values, and the same correlation times. We also present a billiard system that can be used to generate random pulse noise of arbitrary statistical properties. The particle dynamics is considered in terms of delta and wide pulses simultaneously. The results of numerical experiments with the billiard s…

PhysicsSettore FIS/02 - Fisica Teorica Modelli E Metodi MatematiciStochastic processGeneral MathematicsApplied MathematicsGeneral Physics and AstronomySpectral densityStatistical and Nonlinear PhysicsPoisson distributionRenewal processPulse (physics)symbols.namesakeBilliard-like systemsStochastic processessymbolsHardware random number generatorFluctuation phenomenaStatistical physicsRenewal theoryHardware random number generatorDynamical billiardsSuper-Poisson statisticsGenerator (mathematics)Chaos, Solitons & Fractals
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Convergence of Markov Chains

2020

We consider a Markov chain X with invariant distribution π and investigate conditions under which the distribution of X n converges to π as n→∞. Essentially it is necessary and sufficient that the state space of the chain cannot be decomposed into subspaces that the chain does not leave, or that are visited by the chain periodically; e.g., only for odd n or only for even n.

CombinatoricsMarkov chain mixing timeMarkov chainChain (algebraic topology)Markov renewal processBalance equationAdditive Markov chainMarkov propertyExamples of Markov chainsMathematics
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Estimating finite mixtures of semi-Markov chains: an application to the segmentation of temporal sensory data

2019

Summary In food science, it is of great interest to obtain information about the temporal perception of aliments to create new products, to modify existing products or more generally to understand the mechanisms of perception. Temporal dominance of sensations is a technique to measure temporal perception which consists in choosing sequentially attributes describing a food product over tasting. This work introduces new statistical models based on finite mixtures of semi-Markov chains to describe data collected with the temporal dominance of sensations protocol, allowing different temporal perceptions for a same product within a population. The identifiability of the parameters of such mixtur…

futureStatistics and ProbabilityFOS: Computer and information sciencesGamma distributionmiceComputer sciencemedia_common.quotation_subjectPopulationdominancecomputer.software_genreStatistics - Applications01 natural sciencesMethodology (stat.ME)modelsExpectation-maximization algorithmModel-based clustering010104 statistics & probability0404 agricultural biotechnology[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Bayesian information criterionPerceptionExpectation–maximization algorithmApplications (stat.AP)Temporal dominance of sensations[MATH]Mathematics [math]0101 mathematicseducationStatistics - Methodologymedia_common2. Zero hungereducation.field_of_studyMarkov chainMarkov renewal processStatistical model04 agricultural and veterinary sciencesidentifiabilityMixture modelBayesian information criterion040401 food science[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]IdentifiabilityPenalized likelihoodData miningStatistics Probability and UncertaintycomputertdsCategorical time seriessensations
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ON HIGH-SKILL AND LOW-SKILL EQUILIBRIA: A MARKOV CHAIN APPROACH

2006

In this paper we propose to study the dynamics of human capital accumulation by means of a Markov chain. We identify the conditions for the emergence of ergodic and nonergodic dynamics, and relate them to various characteristics of an economic system. The model may generate high-skill and low-skill equilibria as well as intermediate situations. Policy implications are also discussed.

MicroeconomicsEconomics and EconometricsMarkov chainMarkov renewal processFinancial economicsEconomicsErgodic theoryHigh skillHuman capitalMetroeconomica
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Disorder relevance for the random walk pinning model in dimension 3

2011

We study the continuous time version of the random walk pinning model, where conditioned on a continuous time random walk Y on Z^d with jump rate \rho>0, which plays the role of disorder, the law up to time t of a second independent random walk X with jump rate 1 is Gibbs transformed with weight e^{\beta L_t(X,Y)}, where L_t(X,Y) is the collision local time between X and Y up to time t. As the inverse temperature \beta varies, the model undergoes a localization-delocalization transition at some critical \beta_c>=0. A natural question is whether or not there is disorder relevance, namely whether or not \beta_c differs from the critical point \beta_c^{ann} for the annealed model. In Birkner a…

Statistics and Probability60K35 82B4482B44Probability (math.PR)Random mediaGeometryMarginal disorderFractional moment methodMean estimationMathematics::Probability60K35Local limit theoremFOS: MathematicsCollision local timeDisordered pinning modelsStatistics Probability and UncertaintyRandom walksHumanitiesRenewal processes with infinite meanMathematics - ProbabilityMathematicsAnnales de l'Institut Henri Poincaré, Probabilités et Statistiques
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Juggler's exclusion process

2012

Juggler's exclusion process describes a system of particles on the positive integers where particles drift down to zero at unit speed. After a particle hits zero, it jumps into a randomly chosen unoccupied site. We model the system as a set-valued Markov process and show that the process is ergodic if the family of jump height distributions is uniformly integrable. In a special case where the particles jump according to a set-avoiding memoryless distribution, the process reaches its equilibrium in finite nonrandom time, and the equilibrium distribution can be represented as a Gibbs measure conforming to a linear gravitational potential.

Statistics and Probabilityset-valued Markov processmaximum entropy60K35 82C41General Mathematics82C41FOS: Physical sciencesMarkov process01 natural sciencespositive recurrencesymbols.namesakeGravitational potentialMarkov renewal process0103 physical sciencesjuggling patternFOS: MathematicsErgodic theory0101 mathematicsGibbs measureMathematical PhysicsMathematicsDiscrete mathematicsnoncolliding random walkProbability (math.PR)ta111010102 general mathematicsErgodicityMathematical analysisExclusion processMathematical Physics (math-ph)Gibbs measureDistribution (mathematics)set-avoiding memoryless distribution60K35Jumpsymbolsergodicity010307 mathematical physicsStatistics Probability and UncertaintyMathematics - Probability
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