Search results for "Branching process"

showing 10 items of 12 documents

Poisson convergence on continuous time branching random walks and multistage carcinogenesis.

1982

A theorem for Poisson convergence on realizations of two-dimensional Branching Random Walks with an underlying continuous time Markov Branching Process is proved. This result can be used to gain an approximation for the number of cells having sustained a certain deficiency after a long time in multistage carcinogenesis.

Multistage carcinogenesisTime FactorsMarkov chainApplied MathematicsPoisson distributionRandom walkAgricultural and Biological Sciences (miscellaneous)Models BiologicalCombinatoricsBranching (linguistics)symbols.namesakeCell Transformation NeoplasticBranching random walkModeling and SimulationNeoplasmsConvergence (routing)symbolsApplied mathematicsAnimalsHumansMathematicsMathematicsBranching processJournal of mathematical biology
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Jet evolution in a dense medium: event-by-event fluctuations and multi-particle correlations

2017

International audience; We study the gluon distribution produced via successive medium-induced branchings by an energetic jet propagating through a weakly-coupled quark-gluon plasma. We show that under suitable approximations, the jet evolution is a Markovian stochastic process, which is exactly solvable. For this process, we construct exact analytic solutions for all the n-point correlation functions describing the gluon distribution in the space of energy [M. A. Escobedo, E. Iancu, Event-by-event fluctuations in the medium-induced jet evolution, JHEP 05 (2016) 008. arXiv: arXiv:1601.03629 , doi: http://dx.doi.org/10.1007/JHEP05(2016)008 , M. A. Escobedo, E. Iancu, Multi-particle correlati…

Nuclear and High Energy PhysicsParticle physicsmedia_common.quotation_subjectenergy lossMarkov chainKNOformula01 natural sciencesAsymmetryStandard deviationjet0103 physical sciencespropagationscaling: KNOmultiplicityStatistical physicscorrelation function010306 general physicsScalingquark gluon: plasmaBranching processmedia_commonPhysicsLarge Hadron Collidergluon: distribution functionta114Markovian stochastic process010308 nuclear & particles physicsStochastic processfluctuationdijet: asymmetryPlasmajet: asymmetrynucleus nucleus: scatteringGluonwide-anglepath lengthCERN LHC Colljet: energy lossnuclear mattercorrelationevolution equation[PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph]High Energy Physics::Experimentheavy ion: colliding beamsPhenomenology (particle physics)jet evolution
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Including Covariates in the ETAS Model Triggered Seismicity

2020

The paper proposes a stochastic process that improves the assessment of seismic events in space and time, considering a contagion model (branching process) within a regression-like framework to take covariates into account. The proposed approach develops the Forward Likelihood for prediction (FLP) method for estimating the ETAS model, including covariates in the model specification of the epidemic component. A simulation study is carried out for analysing the misspecification model effect under several scenarios. Also an application to the Italian catalogue is reported, together with the reference to the developed R package.

R packageSpecificationSpacetimeComputer scienceStochastic processComponent (UML)CovariateEconometricsStatistics::MethodologyInduced seismicityBranching processSSRN Electronic Journal
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A GALTON-WATSON BRANCHING PROCESS IN VARYING ENVIRONMENTS WITH ESSENTIALLY CONSTANT OFFSPRING MEANS AND TWO RATES OF GROWTH1

1983

Summary A Galton-Watson process in varying environments (Zn), with essentially constant offspring means, i.e. E(Zn)/mnα∈(0, ∞), and exactly two rates of growth is constructed. The underlying sample space Ω can be decomposed into parts A and B such that (Zn)n grows like 2non A and like mnon B (m > 4).

Statistics and ProbabilityCombinatoricsGalton watsonDiscrete mathematicsOffspringSample spaceConstant (mathematics)MathematicsBranching processAustralian Journal of Statistics
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A Galton–Watson process with a threshold

2016

Abstract In this paper we study a special class of size dependent branching processes. We assume that for some positive integer K as long as the population size does not exceed level K, the process evolves as a discrete-time supercritical branching process, and when the population size exceeds level K, it evolves as a subcritical or critical branching process. It is shown that this process does die out in finite time T. The question of when the mean value E(T) is finite or infinite is also addressed.

Statistics and ProbabilityGeneral MathematicsPopulation size010102 general mathematicsMean valueProcess (computing)01 natural sciencesGalton–Watson processBranching (linguistics)010104 statistics & probabilityIntegerStatistical physics0101 mathematicsStatistics Probability and UncertaintyFinite timeMathematicsBranching processJournal of Applied Probability
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Including covariates in a space-time point process with application to seismicity

2020

AbstractThe paper proposes a spatio-temporal process that improves the assessment of events in space and time, considering a contagion model (branching process) within a regression-like framework to take covariates into account. The proposed approach develops the forward likelihood for prediction method for estimating the ETAS model, including covariates in the model specification of the epidemic component. A simulation study is carried out for analysing the misspecification model effect under several scenarios. Also an application to the Italian seismic catalogue is reported, together with the reference to the developed R package.

Statistics and ProbabilityMathematical optimization010504 meteorology & atmospheric sciencesSpacetimeComputer scienceSpace timeSpace-time point processes ETAS model R package for seismic datacovariatesProcess (computing)01 natural sciencesPoint process010104 statistics & probabilitySpecificationComponent (UML)Covariate0101 mathematicsStatistics Probability and Uncertainty0105 earth and related environmental sciencesBranching process
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Non-parametric Estimation of the Death Rate in Branching Diffusions

2002

We consider finite systems of diffusing particles in R with branching and immigration. Branching of particles occurs at position dependent rate. Under ergodicity assumptions, we estimate the position-dependent branching rate based on the observation of the particle process over a time interval [0, t]. Asymptotics are taken as t → ∞. We introduce a kernel-type procedure and discuss its asymptotic properties with the help of the local time for the particle configuration. We compute the minimax rate of convergence in squared-error loss over a range of Holder classes and show that our estimator is asymptotically optimal.

Statistics and ProbabilityParticle systemAsymptotically optimal algorithmRate of convergenceErgodicityCalculusEstimatorApplied mathematicsStatistics Probability and UncertaintyMinimaxPoint processMathematicsBranching processScandinavian Journal of Statistics
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Infinite rate mutually catalytic branching in infinitely many colonies: The longtime behavior

2012

Consider the infinite rate mutually catalytic branching process (IMUB) constructed in [Infinite rate mutually catalytic branching in infinitely many colonies. Construction, characterization and convergence (2008) Preprint] and [Ann. Probab. 38 (2010) 479-497]. For finite initial conditions, we show that only one type survives in the long run if the interaction kernel is recurrent. On the other hand, under a slightly stronger condition than transience, we show that both types can coexist.

Statistics and ProbabilityPure mathematicsProbability (math.PR)coexistenceType (model theory)Characterization (mathematics)Branching (polymer chemistry)Trotter productstochastic differential equationsLévy noisesegregation of typesStochastic differential equationKernel (algebra)Mutually catalytic branching60G1760K35Convergence (routing)FOS: Mathematics60J6560J55PreprintStatistics Probability and UncertaintyMathematics - ProbabilityMathematicsBranching processThe Annals of Probability
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A PHASE TRANSITION FOR LARGE VALUES OF BIFURCATING AUTOREGRESSIVE MODELS

2019

We describe the asymptotic behavior of the number $$Z_n[a_n,\infty )$$ of individuals with a large value in a stable bifurcating autoregressive process, where $$a_n\rightarrow \infty $$ . The study of the associated first moment is equivalent to the annealed large deviation problem of an autoregressive process in a random environment. The trajectorial behavior of $$Z_n[a_n,\infty )$$ is obtained by the study of the ancestral paths corresponding to the large deviation event together with the environment of the process. This study of large deviations of autoregressive processes in random environment is of independent interest and achieved first. The estimates for bifurcating autoregressive pr…

Statistics and Probability[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]Phase transitionrandom environmentGeneral Mathematicsmedia_common.quotation_subjectmoderate deviationslimit-theoremsmarkov-chainsStatistics::Other StatisticsBranching processdeviation inequalities92D2501 natural sciencesAsymmetry010104 statistics & probability[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Convergence (routing)[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]Applied mathematics60C05[MATH]Mathematics [math]0101 mathematicsautoregressive process60J20lawMathematicsBranching processmedia_commonEvent (probability theory)parametersconvergenceMarkov chain010102 general mathematics[MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO][MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Large deviationslarge deviations Mathematics Subject Classification (2010): 60J8060K37Autoregressive modelcellsLarge deviations theoryStatistics Probability and Uncertaintyasymmetry60F10
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ETAS Space–Time Modeling of Chile Triggered Seismicity Using Covariates: Some Preliminary Results

2021

Chilean seismic activity is one of the strongest in the world. As already shown in previous papers, seismic activity can be usefully described by a space–time branching process, such as the ETAS (Epidemic Type Aftershock Sequences) model, which is a semiparametric model with a large time-scale component for the background seismicity and a small time-scale component for the triggered seismicity. The use of covariates can improve the description of triggered seismicity in the ETAS model, so in this paper, we study the Chilean seismicity separately for the North and South area, using some GPS-related data observed together with ordinary catalog data. Our results show evidence that the use of s…

Technologymodel selectionQH301-705.5QC1-999Induced seismicityPhysics::Geophysicssemiparametric modelComponent (UML)CovariateGeneral Materials Sciencetriggered seismicityBiology (General)InstrumentationQD1-999AftershockBranching processFluid Flow and Transfer ProcessesProcess Chemistry and TechnologySpace timeModel selectionTPhysicsGeneral EngineeringcovariatesEngineering (General). Civil engineering (General)Computer Science ApplicationsSemiparametric modelETAS modelChemistrycovariatesemiparametric modelsTA1-2040GeologySeismologyApplied Sciences
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