Sojourns, Extremes, and Self-Intersections of Stochastic Processes

Abstract

The subjects of this research are certain probabilistic properties of real and vector valued random functions X(t), where t is a generalized time parameter taking values in a subset T of Euclidean space. The distributions of three functionals of the random function X are studied. For any Borel set A in the range, the sojourn time of X in A is defined as the measure of the subset of the points t in T such that X(t) belongs to A. The self-intersection set of X is the subset of the set of points (s,t) in the product space of T such that s = t and X(s) = X(t). Finally, for a real valued random function X, the extreme value is the functional equal to the maximum value of X on the domain T. The research is concerned with the determination of the distributions of these functionals under various hypotheses about the probabilistic structure of X. It is assumed here that the random function is Gaussian or Markovian. Stochastic process, Extreme value, Sojourn time, Local time, Limiting distribution, Self- intersections of paths, Gaussian process, Markov process.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1992
Accession Number
ADA257251

Entities

People

  • Simeon M. Berman

Organizations

  • New York University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Applied Mathematics
  • Covariance
  • Data Science
  • Distribution Functions
  • Gaussian Processes
  • Information Science
  • Integrals
  • Markov Processes
  • Mathematics
  • Military Research
  • New York
  • Normal Distribution
  • Probability
  • Probability Density Functions
  • Random Variables
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Graph Algorithms and Convex Optimization.
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • Space