On First Passage Times and Differential Equations,

Abstract

Practical and theoretical considerations in computing first passage time statistics are considered. We are motivated by first passage times as models of failure times. In Section 1, the relevance of first passage time distrbutions as failure time models is indicated. Also, the spectral series expansion solution to the backward equation is introduced. In Section 2, algorithms for approximating w(x,t) are obtained. In particular, the infinite spectral expansion of rw(x,t) is approximated by an n-term sub-expansion which matches the first n-1 moments. Proofs validating the spectral expansion and the related approximation scheme are given in the Appendix. In Sections 3 and 4, methods are given for obtaining the eigenvalues and first passage moments, necessary for computing approximations to w(x,t). In Section 5, computational issues related to calculating the moment generating function are considered. Sections 6 and 7 include theoretical complements about first passage times. In particular, the moment generating function is shown to possess an interesting representation having exponential form (cf equations (7.1)). This exponential representation is related to asymptotic expansions used in analyzing perturbations of certain second-order differential equations.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1986
Accession Number
ADA174648

Entities

People

  • Michael L. Wenocur

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Boundaries
  • Boundary Value Problems
  • Brownian Motion
  • Computational Fluid Dynamics
  • Computational Science
  • Differential Equations
  • Diffusion
  • Eigenvalues
  • Eigenvectors
  • Equations
  • Power Series
  • Probability
  • Random Variables
  • Security
  • Statistics
  • Stochastic Processes
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Fluid Dynamics.
  • Statistical inference.