Search results for "Mathematical analysis"

showing 10 items of 2409 documents

Non-Gaussian probability density function of SDOF linear structures under wind actions

1998

Abstract Wind velocity is usually analytically described adding a static mean term to a zero mean fluctuation stationary process. The corresponding aerodynamic alongwind force acting on a single degree of freedom (SDOF) structure can be considered as a sum of three terms proportional to the mean wind velocity, to the product between mean and fluctuating part of the wind velocity and to the square power of the fluctuating wind velocity, respectively. The latter term, often neglected in the literature, is responsible for the non-Gaussian behaviour of the response. In this paper a method for the evaluation of the stationary probability density function of SDOF structures subjected to non-Gauss…

Stationary processStationary distributionSeries (mathematics)Renewable Energy Sustainability and the EnvironmentMechanical EngineeringGaussianMathematical analysisProbability density functionWind speedAerodynamic forcesymbols.namesakesymbolsSeries expansionCivil and Structural EngineeringMathematicsAlongwind response; Probability density function; Non-Gaussian stochastic analysis
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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
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On fractional diffusion and continuous time random walks

2003

Abstract A continuous time random walk model is presented with long-tailed waiting time density that approaches a Gaussian distribution in the continuum limit. This example shows that continuous time random walks with long time tails and diffusion equations with a fractional time derivative are in general not asymptotically equivalent.

Statistics and ProbabilityAnomalous diffusionGaussianMathematical analysisCondensed Matter PhysicsRandom walkFractional calculussymbols.namesakeDistribution (mathematics)Time derivativesymbolsLimit (mathematics)Continuous-time random walkMathematicsPhysica A: Statistical Mechanics and its Applications
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Weighted bounded mean oscillation applied to backward stochastic differential equations

2015

Abstract We deduce conditional L p -estimates for the variation of a solution of a BSDE. Both quadratic and sub-quadratic types of BSDEs are considered, and using the theory of weighted bounded mean oscillation we deduce new tail estimates for the solution ( Y , Z ) on subintervals of [ 0 , T ] . Some new results for the decoupling technique introduced in Geiss and Ylinen (2019) are obtained as well and some applications of the tail estimates are given.

Statistics and ProbabilityApplied MathematicsProbability (math.PR)010102 general mathematicsMathematical analysis01 natural sciencesBSDEsBounded mean oscillationdecoupling010104 statistics & probabilityStochastic differential equationvärähtelytQuadratic equationJohn-Nirenberg theoremtail estimatesModeling and Simulation60H10 60G99FOS: MathematicsDecoupling (probability)weighted bounded mean oscillation0101 mathematicsdifferentiaaliyhtälötMathematics - Probabilitystokastiset prosessitMathematicsStochastic Processes and their Applications
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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
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Isotropic stochastic flow of homeomorphisms on Rd associated with the critical Sobolev exponent

2008

Abstract We consider the critical Sobolev isotropic Brownian flow in R d ( d ≥ 2 ) . On the basis of the work of LeJan and Raimond [Y. LeJan, O. Raimond, Integration of Brownian vector fields, Ann. Probab. 30 (2002) 826–873], we prove that the corresponding flow is a flow of homeomorphisms. As an application, we construct an explicit solution, which is also unique in a certain space, to the stochastic transport equation when the associated Gaussian vector fields are divergence free.

Statistics and ProbabilityBasis (linear algebra)Stochastic processApplied MathematicsMathematical analysisSpace (mathematics)Sobolev spaceStochastic differential equationMathematics::ProbabilityFlow (mathematics)Modeling and SimulationVector fieldBrownian motionMathematicsStochastic Processes and their Applications
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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
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Other 2N− 2 parameters solutions of the NLS equation and 2N+ 1 highest amplitude of the modulus of theNth order AP breather

2015

In this paper, we construct new deformations of the Akhmediev-Peregrine (AP) breather of order N (or APN breather) with real parameters. Other families of quasirational solutions of the nonlinear Schrodinger (NLS) equation are obtained. We evaluate the highest amplitude of the modulus of the AP breather of order N; we give the proof that the highest amplitude of the APN breather is equal to . We get new formulas for the solutions of the NLS equation, which are different from these already given in previous works. New solutions for the order 8 and their deformations according to the parameters are explicitly given. We simultaneously get triangular configurations and isolated rings. Moreover,…

Statistics and ProbabilityBreatherMathematical analysisGeneral Physics and AstronomyModulusStatistical and Nonlinear PhysicsConcentric ringNonlinear systemsymbols.namesakeNonlinear Sciences::Exactly Solvable and Integrable SystemsAmplitudeModeling and SimulationsymbolsOrder (group theory)Nonlinear Sciences::Pattern Formation and SolitonsMathematical PhysicsSchrödinger's catMathematicsJournal of Physics A: Mathematical and Theoretical
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Hölder Continuity up to the Boundary of Minimizers for Some Integral Functionals with Degenerate Integrands

2007

We study qualitative properties of minimizers for a class of integral functionals, defined in a weighted space. In particular we obtain Hölder regularity up to the boundary for the minimizers of an integral functional of high order by using an interior local regularity result and a modified Moser method with special test function.

Statistics and ProbabilityClass (set theory)Article Subjectlcsh:MathematicsApplied MathematicsMathematical analysisDegenerate energy levelsBoundary (topology)Hölder conditionlcsh:QA1-939Modeling and SimulationTest functions for optimizationlcsh:QHigh orderlcsh:ScienceWeighted spaceMathematicsJournal of Applied Mathematics and Stochastic Analysis
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Flow of Homeomorphisms and Stochastic Transport Equations

2007

Abstract We consider Stratonovich stochastic differential equations with drift coefficient A 0 satisfying only the condition of continuity where r is a positive C 1 function defined on a neighborhood ]0, c 0] of 0 such that (Osgood condition), and s → r(s) is decreasing while s → sr(s 2) is increasing. We prove that the equation defines a flow of homeomorphisms if the diffusion coefficients A 1,…, A N are in . If , we prove limit theorems for Wong–Zakai approximation as well as for regularizing the drift A 0. As an application, we solve a class of stochastic transport equations.

Statistics and ProbabilityClass (set theory)Stochastic differential equationFlow (mathematics)Stochastic processApplied MathematicsMathematical analysisLimit (mathematics)Function (mathematics)Statistics Probability and UncertaintyDiffusion (business)HomeomorphismMathematicsStochastic Analysis and Applications
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