Search results for " function"

showing 10 items of 9395 documents

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

Properties of the elasticity of a continuous random variable. A special look at its behavior and speed of change

2016

ABSTRACTBelzunce et al. (1995) define the elasticity for non negative random variables as the reversed proportional failure rate (RPFR). Veres-Ferrer and Pavia (2012, 2014b) interpret it in economic terms, extending its definition to variables that can also take negative values, and briefly present the role of elasticity in characterizing probability distributions. This paper highlights a set of properties demonstrated by elasticity, which shows many similar properties to the reverse hazard function. This paper pays particular attention to studying the increase/decrease and the speed of change of the elasticity function. These are important properties because of the characterizing role of e…

Statistics and Probability021103 operations researchStochastic process0211 other engineering and technologiesFailure rate02 engineering and technology01 natural sciencesElasticity of a function010104 statistics & probabilitysymbols.namesakeEconometricssymbolsProbability distribution0101 mathematicsElasticity (economics)Fisher informationRandom variableMathematicsCommunications in Statistics - Theory and Methods
researchProduct

ON THE ASYMPTOTIC DISTRIBUTION OF BARTLETT'S Up-STATISTIC

1985

Abstract. In this paper the asymptotic behaviour of Bartlett's Up-statistic for a goodness-of-fit test for stationary processes, is considered. The asymptotic distribution of the test process is given under the assumption that a central limit theorem for the empirical spectral distribution function holds. It is shown that the Up-statistic tends to the supremum of a tied down Brownian motion. By a counterexample we refute the conjecture that this distribution is in general of the Kolmogorov-Smirnov type. The validity of the central limit theorem for the spectral distribution function is then discussed. Finally a goodness-of-fit test for ARMA-processes based on the estimated innovation sequen…

Statistics and ProbabilityAnderson–Darling testApplied MathematicsMathematical analysisV-statisticAsymptotic distributionKolmogorov–Smirnov testEmpirical distribution functionsymbols.namesakeSampling distributionsymbolsTest statisticStatistics Probability and UncertaintyCentral limit theoremMathematicsJournal of Time Series Analysis
researchProduct

Derived variables calculated from similar joint responses: some characteristics and examples

1995

Abstract A technique (Cox and Wermuth, 1992) is reviewed for finding linear combinations of a set of response variables having special relations of linear conditional independence with a set of explanatory variables. A theorem in linear algebra is used both to examine conditions in which the derived variables take a specially simple form and lead to reduced computations. Examples are discussed of medical and psychological investigations in which the method has aided interpretation.

Statistics and ProbabilityApplied MathematicsDesign matrixComputational MathematicsComputational Theory and MathematicsConditional independenceLinear predictor functionLinear algebraCalculusApplied mathematicsMarginal distributionCanonical correlationLinear combinationIndependence (probability theory)MathematicsComputational Statistics & Data Analysis
researchProduct

Time-dependent weak rate of convergence for functions of generalized bounded variation

2016

Let $W$ denote the Brownian motion. For any exponentially bounded Borel function $g$ the function $u$ defined by $u(t,x)= \mathbb{E}[g(x{+}\sigma W_{T-t})]$ is the stochastic solution of the backward heat equation with terminal condition $g$. Let $u^n(t,x)$ denote the corresponding approximation generated by a simple symmetric random walk with time steps $2T/n$ and space steps $\pm \sigma \sqrt{T/n}$ where $\sigma > 0$. For quite irregular terminal conditions $g$ (bounded variation on compact intervals, locally H\"older continuous) the rate of convergence of $u^n(t,x)$ to $u(t,x)$ is considered, and also the behavior of the error $u^n(t,x)-u(t,x)$ as $t$ tends to $T$

Statistics and ProbabilityApproximation using simple random walkweak rate of convergence01 natural sciencesStochastic solution41A25 65M15 (Primary) 35K05 60G50 (Secondary)010104 statistics & probabilityExponential growthFOS: Mathematics0101 mathematicsBrownian motionstokastiset prosessitMathematicsosittaisdifferentiaaliyhtälötApplied MathematicsProbability (math.PR)010102 general mathematicsMathematical analysisfinite difference approximation of the heat equationFunction (mathematics)Rate of convergenceBounded functionBounded variationnumeerinen analyysiapproksimointiStatistics Probability and UncertaintyMathematics - ProbabilityStochastic Analysis and Applications
researchProduct

On first exit times and their means for Brownian bridges

2017

For a Brownian bridge from $0$ to $y$ we prove that the mean of the first exit time from interval $(-h,h), \,\, h>0,$ behaves as $O(h^2)$ when $h \downarrow 0.$ Similar behavior is seen to hold also for the 3-dimensional Bessel bridge. For Brownian bridge and 3-dimensional Bessel bridge this mean of the first exit time has a puzzling representation in terms of the Kolmogorov distribution. The result regarding the Brownian bridge is applied to prove in detail an estimate needed by Walsh to determine the convergence of the binomial tree scheme for European options.

Statistics and ProbabilityBessel processGeneral Mathematics010102 general mathematicsMathematical analysisProbability (math.PR)Brownian bridge01 natural sciencesBridge (interpersonal)010104 statistics & probabilitysymbols.namesakeDistribution (mathematics)Diffusion processMathematics::ProbabilitysymbolsFOS: MathematicsBinomial options pricing model0101 mathematicsStatistics Probability and UncertaintyMathematics - ProbabilityBessel functionBrownian motionMathematics
researchProduct

Response functions in multicomponent Luttinger liquids

2012

We derive an analytic expression for the zero temperature Fourier transform of the density-density correlation function of a multicomponent Luttinger liquid with different velocities. By employing Schwinger identity and a generalized Feynman identity exact integral expressions are derived, and approximate analytical forms are given for frequencies close to each component singularity. We find power-like singularities and compute the corresponding exponents. Numerical results are shown for the case of three components.

Statistics and ProbabilityBosonizationFOS: Physical sciences01 natural sciences010305 fluids & plasmassymbols.namesakeIdentity (mathematics)Condensed Matter - Strongly Correlated ElectronsSingularityCorrelation functionLuttinger liquid0103 physical sciencesFeynman diagramLuttinger liquids (theory)010306 general physics71.10.Pm 02.30.Nw 02.30.UuMathematical physicsPhysicsStrongly Correlated Electrons (cond-mat.str-el)Statistical and Nonlinear PhysicsFourier transformsymbolsGravitational singularityStatistics Probability and Uncertaintybosonization[PHYS.COND.CM-SCE]Physics [physics]/Condensed Matter [cond-mat]/Strongly Correlated Electrons [cond-mat.str-el]
researchProduct

Breathers and solitons of generalized nonlinear Schrödinger equations as degenerations of algebro-geometric solutions

2011

We present new solutions in terms of elementary functions of the multi-component nonlinear Schr\"odinger equations and known solutions of the Davey-Stewartson equations such as multi-soliton, breather, dromion and lump solutions. These solutions are given in a simple determinantal form and are obtained as limiting cases in suitable degenerations of previously derived algebro-geometric solutions. In particular we present for the first time breather and rational breather solutions of the multi-component nonlinear Schr\"odinger equations.

Statistics and ProbabilityBreatherMathematics::Analysis of PDEsGeneral Physics and AstronomyFOS: Physical sciences01 natural sciences010305 fluids & plasmasSchrödinger equationsymbols.namesakeMathematics - Analysis of PDEsSimple (abstract algebra)[MATH.MATH-MP]Mathematics [math]/Mathematical Physics [math-ph]0103 physical sciencesFOS: MathematicsElementary function[MATH.MATH-MP] Mathematics [math]/Mathematical Physics [math-ph]010306 general physicsNonlinear Sciences::Pattern Formation and SolitonsMathematical PhysicsMathematical physicsPhysics[ MATH.MATH-MP ] Mathematics [math]/Mathematical Physics [math-ph]Statistical and Nonlinear PhysicsLimitingMathematical Physics (math-ph)Mathematics::Spectral TheoryNonlinear systemNonlinear Sciences::Exactly Solvable and Integrable SystemsModeling and SimulationsymbolsAnalysis of PDEs (math.AP)
researchProduct