Search results for "probability"

showing 10 items of 3417 documents

Stability measures in metastable states with Gaussian colored noise

2009

We present a study of the escape time from a metastable state of an overdamped Brownian particle, in the presence of colored noise generated by Ornstein-Uhlenbeck process. We analyze the role of the correlation time on the enhancement of the mean first passage time through a potential barrier and on the behavior of the mean growth rate coefficient as a function of the noise intensity. We observe the noise enhanced stability effect for all the initial unstable states used, and for all values of the correlation time $\tau_c$ investigated. We can distinguish two dynamical regimes characterized by weak and strong correlated noise respectively, depending on the value of $\tau_c$ with respect to …

Statistical Mechanics (cond-mat.stat-mech)FOS: Physical sciencesFunction (mathematics)Stability (probability)Colors of noiseStochastic Mechanics Noise Nonlinear systemsMetastabilityRectangular potential barrierStatistical physicsGrowth rateFirst-hitting-time modelBrownian motionCondensed Matter - Statistical MechanicsMathematics
researchProduct

Noise-enhanced stability of periodically driven metastable states

2000

We study the effect of noise-enhanced stability of periodically driven metastable states in a system described by piecewise linear potential. We find that the growing of the average escape time with the intensity of the noise is depending on the initial condition of the system. We analytically obtain the condition for the noise enhanced stability effect and verify it by numerical simulations.

Statistical Mechanics (cond-mat.stat-mech)FOS: Physical sciencesMechanicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksStability (probability)Piecewise linear functionControl theoryMetastabilityInitial value problemNoise (radio)Intensity (heat transfer)Condensed Matter - Statistical MechanicsMathematics
researchProduct

Signatures of noise-enhanced stability in metastable state

2005

The lifetime of a metastable state in the transient dynamics of an overdamped Brownian particle is analyzed, both in terms of the mean first passage time and by means of the mean growth rate coefficient. Both quantities feature non monotonic behaviors as a function of the noise intensity, and are independent signatures of the noise enhanced stability effect. They can therefore be alternatively used to evaluate and estimate the presence of this phenomenon, which characterizes metastability in nonlinear physical systems.

Statistical Mechanics (cond-mat.stat-mech)Physical systemFOS: Physical sciencesNoise (electronics)Stability (probability)Nonlinear systemMetastabilityQuantum mechanicsStatistical physicsTransient (oscillation)noise-enhanced stability Circuit resonance Magnetic resonance vibrational resonanceFirst-hitting-time modelBrownian motionCondensed Matter - Statistical MechanicsMathematics
researchProduct

Strongly confined fluids: Diverging time scales and slowing down of equilibration

2016

The Newtonian dynamics of strongly confined fluids exhibits a rich behavior. Its confined and unconfined degrees of freedom decouple for confinement length $L \to 0$. In that case and for a slit geometry the intermediate scattering functions $S_{\mu\nu}(q,t)$ simplify, resulting for $(\mu,\nu) \neq (0,0)$ in a Knudsen-gas like behavior of the confined degrees of freedom, and otherwise in $S_{\parallel}(q,t)$, describing the structural relaxation of the unconfined ones. Taking the coupling into account we prove that the energy fluctuations relax exponentially. For smooth potentials the relaxation times diverge as $L^{-3}$ and $L^{-4}$, respectively, for the confined and unconfined degrees of…

Statistical Mechanics (cond-mat.stat-mech)ScatteringDegrees of freedom (physics and chemistry)Pair distribution functionFOS: Physical sciences02 engineering and technologyCondensed Matter - Soft Condensed Matter021001 nanoscience & nanotechnologyCoupling (probability)01 natural sciencesNewtonian dynamicsQuantum mechanics0103 physical sciencesRelaxation (physics)Soft Condensed Matter (cond-mat.soft)010306 general physics0210 nano-technologyPair potentialCondensed Matter - Statistical MechanicsEnergy (signal processing)Mathematics
researchProduct

Statistical Properties of Statistical Ensembles of Stock Returns

1999

We select n stocks traded in the New York Stock Exchange and we form a statistical ensemble of daily stock returns for each of the k trading days of our database from the stock price time series. We analyze each ensemble of stock returns by extracting its first four central moments. We observe that these moments are fluctuating in time and are stochastic processes themselves. We characterize the statistical properties of central moments by investigating their probability density function and temporal correlation properties.

Statistical ensemblePhysics::Physics and SocietyStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)Stochastic processFinancial economicsQuantitative Finance - Statistical FinanceFOS: Physical sciencesProbability density functionTemporal correlationStock priceFOS: Economics and businessStock exchangeComputer Science::Computational Engineering Finance and ScienceEconomicsEconometricsGeneral Economics Econometrics and FinanceFinanceStock (geology)Condensed Matter - Statistical Mechanics
researchProduct

Variety and volatility in financial markets

2000

We study the price dynamics of stocks traded in a financial market by considering the statistical properties both of a single time series and of an ensemble of stocks traded simultaneously. We use the $n$ stocks traded in the New York Stock Exchange to form a statistical ensemble of daily stock returns. For each trading day of our database, we study the ensemble return distribution. We find that a typical ensemble return distribution exists in most of the trading days with the exception of crash and rally days and of the days subsequent to these extreme events. We analyze each ensemble return distribution by extracting its first two central moments. We observe that these moments are fluctua…

Statistical ensembleStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)Stochastic processFinancial marketQuantitative Finance - Statistical FinanceFOS: Physical sciencesProbability density functionRelative strengthFOS: Economics and businessStock exchangeEconometricsVolatility (finance)Condensed Matter - Statistical MechanicsStock (geology)MathematicsPhysical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
researchProduct

$L_2$-variation of L\'{e}vy driven BSDEs with non-smooth terminal conditions

2016

We consider the $L_2$-regularity of solutions to backward stochastic differential equations (BSDEs) with Lipschitz generators driven by a Brownian motion and a Poisson random measure associated with a L\'{e}vy process $(X_t)_{t\in[0,T]}$. The terminal condition may be a Borel function of finitely many increments of the L\'{e}vy process which is not necessarily Lipschitz but only satisfies a fractional smoothness condition. The results are obtained by investigating how the special structure appearing in the chaos expansion of the terminal condition is inherited by the solution to the BSDE.

Statistics and Probability$L_{2}$-regularityPure mathematicsSmoothness (probability theory)Malliavin calculus010102 general mathematicsChaos expansionPoisson random measureFunction (mathematics)Lipschitz continuityMalliavin calculus01 natural sciencesLévy process010104 statistics & probabilityStochastic differential equationMathematics::ProbabilityLévy processesbackward stochastic differential equations0101 mathematicsL 2 -regularityBrownian motionMathematics - ProbabilityMathematics
researchProduct

Conditional convex orders and measurable martingale couplings

2014

Strassen's classical martingale coupling theorem states that two real-valued random variables are ordered in the convex (resp.\ increasing convex) stochastic order if and only if they admit a martingale (resp.\ submartingale) coupling. By analyzing topological properties of spaces of probability measures equipped with a Wasserstein metric and applying a measurable selection theorem, we prove a conditional version of this result for real-valued random variables conditioned on a random element taking values in a general measurable space. We also provide an analogue of the conditional martingale coupling theorem in the language of probability kernels and illustrate how this result can be appli…

Statistics and Probability01 natural sciencesStochastic ordering010104 statistics & probabilitysymbols.namesakeMathematics::ProbabilityStrassen algorithmWasserstein metricmartingale couplingvektorit (matematiikka)FOS: MathematicsApplied mathematics0101 mathematicsstokastiset prosessitMathematicsProbability measurekytkentäconvex stochastic ordermatematiikka010102 general mathematicsProbability (math.PR)Random elementMarkov chain Monte Carloconditional couplingincreasing convex stochastic orderpointwise couplingsymbols60E15probability kernelMartingale (probability theory)Random variableMathematics - Probability
researchProduct

Author response to the contributors to the discussion on “A critical evaluation of the current ‘p -value controversy’”

2017

Statistics and Probability010104 statistics & probability03 medical and health sciences0302 clinical medicineMEDLINE030212 general & internal medicineGeneral Medicine0101 mathematicsStatistics Probability and UncertaintyCurrent (fluid)Positive economicsPsychology01 natural sciencesBiometrical Journal
researchProduct

Discussion of "modern statistics of spatial point processes"

2007

The paper ‘Modern statistics for spatial point processes' by Jesper Møller and Rasmus P. Waagepetersen is based on a special invited lecture given by the authors at the 21st Nordic Conference on Mathematical Statistics, held at Rebild, Denmark, in June 2006. At the conference, Antti Penttinen and Eva B. Vedel Jensen were invited to discuss the paper. We here present the comments from the two invited discussants and from a number of other scholars, as well as the authors' responses to these comments. Below Figure 1, Figure 2, etc., refer to figures in the paper under discussion, while Figure A, Figure B, etc., refer to figures in the current discussion. All numbered sections and formulas ref…

Statistics and Probability010104 statistics & probabilityPoint (typography)[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]010102 general mathematicsStatisticsMathematical statistics[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]0101 mathematicsStatistics Probability and Uncertainty01 natural sciencesPoint processMathematics
researchProduct