Dispersion points for linear sets and approximate moduli for some stochastic processes

Author:

Geman Donald

Abstract

Let Γ [ 0 , 1 ] \Gamma \, \in \,[0,\,1] be Lebesgue measurable; then Γ \Gamma has Lebesgue density 0 at the origin if and only if \[ Γ t 1 Ψ ( t 1 meas { Γ ( 0 , t ) } ) d t > \int _\Gamma {{t^{ - 1}}\Psi ({t^{ - 1}}\,{\text {meas}}} \{ \Gamma \, \cap \,(0,\,t)\} )\,dt\, > \,\infty \] for some continuous, strictly increasing function Ψ ( t ) ( 0 t 1 ) \Psi (t)\,(0\, \leqslant \,t\, \leqslant \,1) with Ψ ( 0 ) = 0 \Psi (0)\, = \,0 . This result is applied to the local growth of certain Gaussian (and other) proceses { X t , t 0 } \{ {X_t},\,t\, \geqslant \,0\} as follows: we find continuous, increasing functions ϕ ( t ) \phi (t) and η ( t ) ( t 0 ) \eta (t)\,(t\, \geqslant \,0) such that, with probability one, the set { t : η ( t ) | X t X 0 | ϕ ( t ) } \{ t:\eta (t)\, \leqslant \,\left | {{X_t}\, - \,{X_0}} \right |\, \leqslant \,\phi (t)\} has density 1 at the origin.

Publisher

American Mathematical Society (AMS)

Subject

Applied Mathematics,General Mathematics

Reference11 articles.

1. Local nondeterminism and local times of Gaussian processes;Berman, Simeon M.;Indiana Univ. Math. J.,1973

2. Occupation densities;Geman, Donald;Ann. Probab.,1980

3. On the increments of multidimensional random fields;Geman, Donald;Ann. Probability,1978

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