Search results for " time"

showing 10 items of 3005 documents

Statistics of return times for weighted maps of the interval

2000

For non markovian, piecewise monotonic maps of the interval associated to a potential, we prove that the law of the entrance time in a cylinder, when renormalized by the measure of the cylinder, converges to an exponential law for almost all cylinders. Thanks to this result, we prove that the fluctuations of Rn, first return time in a cylinder, are lognormal.

Statistics and ProbabilityMathematical analysisMarkov processMonotonic functionCylinder (engine)law.inventionPhysics::Fluid DynamicsReturn timesymbols.namesakelawLog-normal distributionPiecewisesymbolsStatistics Probability and UncertaintyExponential lawMathematicsAnnales de l'Institut Henri Poincare (B) Probability and Statistics
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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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Forward likelihood-based predictive approach for space-time point processes

2011

Dealing with data from a space–time point process, the estimation of the conditional intensity function is a crucial issue even if a complete definition of a parametric model is not available. In particular, in case of exploratory contexts or if we want to assess the adequacy of a specific parametric model, some kind of nonparametric estimation procedure could be useful. Often, for these purposes kernel estimators are used and the estimation of the intensity function depends on the estimation of bandwidth parameters. In some fields, like for instance the seismological one, predictive properties of the estimated intensity function are pursued. Since a direct ML approach cannot be used, we pr…

Statistics and ProbabilityMathematical optimizationEcological ModelingSpace timespace–time point processesBandwidth (signal processing)Nonparametric statisticsEstimatorStatistical seismologynonparametric estimationPoint processParametric modellikelihood functionSettore SECS-S/01 - StatisticaLikelihood functionpredictive propertieMathematicsEnvironmetrics
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Sequential estimation of a location parameter and powers of a scale parameter from delayed observations

2013

The problem of sequentially estimating a location parameter and powers of a scale parameter is considered in the case when the observations become available at random times. Certain classes of sequential estimation procedures are derived under an invariant balanced loss function and with the observation cost determined by a convex function of the stopping time and the number of observations up to that time.

Statistics and ProbabilityMathematical optimizationSequential estimationLocation parameterStopping timeApplied mathematicsFunction (mathematics)Statistics Probability and UncertaintyInvariant (mathematics)Convex functionScale parameterShape parameterMathematicsStatistica Neerlandica
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Lead-time and overdiagnosis estimation in neuroblastoma screening.

2003

In Germany, neuroblastoma is the most frequent extracranial solid childhood tumour. Its properties made it seem an ideal candidate for screening. A German trial assessed the effect of screening at one year of age from 1995-2001 in a nationwide project. We present here the methods developed for the estimation of lead-time and overdiagnosis in this project. Follow up on 1.5 million screened children and 2.1 million control children is currently available until June 2002. Ascertainment of control cohort cases and false negative cases is complete up to this date. A method for determining an empirical lead-time distribution and overdiagnosis estimate from comparing the age specific incidences in…

Statistics and ProbabilityPediatricsmedicine.medical_specialtyEpidemiologySensitivity and SpecificityCohort StudiesNeuroblastomaAge DistributionGermanyNeuroblastoma screeningBiomarkers TumorMedicineHumansMass ScreeningFalse Positive ReactionsOverdiagnosisMass screeningEstimationbusiness.industryIncidence (epidemiology)IncidenceInfantPopulation SurveillanceCohortbusinessLead timeDemographyCohort studyStatistics in medicine
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Hitting Time Distributions in Financial Markets

2006

We analyze the hitting time distributions of stock price returns in different time windows, characterized by different levels of noise present in the market. The study has been performed on two sets of data from US markets. The first one is composed by daily price of 1071 stocks trade for the 12-year period 1987-1998, the second one is composed by high frequency data for 100 stocks for the 4-year period 1995-1998. We compare the probability distribution obtained by our empirical analysis with those obtained from different models for stock market evolution. Specifically by focusing on the statistical properties of the hitting times to reach a barrier or a given threshold, we compare the prob…

Statistics and ProbabilityPhysics - Physics and SocietyAutoregressive conditional heteroskedasticityStock market modelFOS: Physical sciencesPhysics and Society (physics.soc-ph)Langevin-type equationHeston modelEconophysics; Stock market model; Langevin-type equation; Heston model; Complex SystemsFOS: Economics and businessEconometricsMathematicsGeometric Brownian motionStatistical Finance (q-fin.ST)Actuarial scienceEconophysicFinancial marketHitting timeQuantitative Finance - Statistical FinanceComplex SystemsProbability and statisticsCondensed Matter PhysicsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Heston modelPhysics - Data Analysis Statistics and ProbabilityProbability distributionStock marketData Analysis Statistics and Probability (physics.data-an)
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Modeling interactions between political parties and electors

2017

In this paper we extend some recent results on an operatorial approach to the description of alliances between political parties interacting among themselves and with a basin of electors. In particular, we propose and compare three different models, deducing the dynamics of their related {\em decision functions}, i.e. the attitude of each party to form or not an alliance. In the first model the interactions between each party and their electors are considered. We show that these interactions drive the decision functions towards certain asymptotic values depending on the electors only: this is the {\em perfect party}, which behaves following the electors' suggestions. The second model is an …

Statistics and ProbabilityPhysics - Physics and SocietyDynamical systems theorySpecific timeFOS: Physical sciencesExtension (predicate logic)Physics and Society (physics.soc-ph)Condensed Matter Physics01 natural sciencesDecision making Dynamical systems Quantum models in macroscopic systems010305 fluids & plasmasPoliticsAllianceQuartic function0103 physical sciences010306 general physicsMathematical economicsSettore MAT/07 - Fisica MatematicaMathematics
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One-directional quantum mechanical dynamics and an application to decision making

2020

In recent works we have used quantum tools in the analysis of the time evolution of several macroscopic systems. The main ingredient in our approach is the self-adjoint Hamiltonian $H$ of the system $\Sc$. This Hamiltonian quite often, and in particular for systems with a finite number of degrees of freedom, gives rise to reversible and oscillatory dynamics. Sometimes this is not what physical reasons suggest. We discuss here how to use non self-adjoint Hamiltonians to overcome this difficulty: the time evolution we obtain out of them show a preferable arrow of time, and it is not reversible. Several applications are constructed, in particular in connection to information dynamics.

Statistics and ProbabilityQuantum PhysicsComputer scienceQuantum dynamicsTime evolutionFOS: Physical sciencesCondensed Matter Physicssymbols.namesakeArrow of timesymbolsQuantum dynamics Non self-adjoint Hamiltonian Decision makingMechanical dynamicsInformation dynamicsStatistical physicsHamiltonian (quantum mechanics)Quantum Physics (quant-ph)Finite setQuantumSettore MAT/07 - Fisica Matematica
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An entropic analysis of approximate quantum error correction

2013

The concept of entropy and the correct application of the Second Law of thermodynamics are essential in order to understand the reason why quantum error correction is thermodynamically possible and no violation of the Second Law occurs during its execution. We report in this work our first steps towards an entropic analysis extended to approximate quantum error correction (QEC). Special emphasis is devoted to the link among quantum state discrimination (QSD), quantum information gain, and quantum error correction in both the exact and approximate QEC scenarios.

Statistics and ProbabilityQuantum discordQuantum PhysicsFOS: Physical sciencesCondensed Matter PhysicsQuantum relative entropyTheoretical physicsT-symmetryQuantum error correctionQuantum stateStatistical physicsQuantum informationQuantum Physics (quant-ph)Entropy (arrow of time)Joint quantum entropyMathematics
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On an approximation problem for stochastic integrals where random time nets do not help

2006

Abstract Given a geometric Brownian motion S = ( S t ) t ∈ [ 0 , T ] and a Borel measurable function g : ( 0 , ∞ ) → R such that g ( S T ) ∈ L 2 , we approximate g ( S T ) - E g ( S T ) by ∑ i = 1 n v i - 1 ( S τ i - S τ i - 1 ) where 0 = τ 0 ⩽ ⋯ ⩽ τ n = T is an increasing sequence of stopping times and the v i - 1 are F τ i - 1 -measurable random variables such that E v i - 1 2 ( S τ i - S τ i - 1 ) 2 ∞ ( ( F t ) t ∈ [ 0 , T ] is the augmentation of the natural filtration of the underlying Brownian motion). In case that g is not almost surely linear, we show that one gets a lower bound for the L 2 -approximation rate of 1 / n if one optimizes over all nets consisting of n + 1 stopping time…

Statistics and ProbabilityRandom time netsMeasurable functionStochastic processStochastic integralsApplied MathematicsUpper and lower boundsNatural filtrationCombinatoricsModeling and SimulationStopping timeModelling and SimulationAlmost surelyApproximationBorel measureBrownian motionMathematicsStochastic Processes and their Applications
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