Topics in Stochastic Systems: Failure Time Models, Change-Point Problems, and Sequential Analysis

Abstract

Fundamental progress was made in the sequential and fixed sample detection and estimation of abrupt changes in stochastic systems and in the related problem of adaptive control of dynamical systems with time-varying parameters. Also studied were recursive estimation and adaptive control of linear stochastic systems, where an essentially complete asymptotic solution was developed for the problem of adaptive estimation of inputs to keep the output of a system close to a fixed target. Advances were made in regression analysis of censored failure time data, inference in nonlinear regression models, and sequential analysis. Related probability theory involving boundary crossing problems and approximate distributions of maxima of random fields also was developed.

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Document Details

Document Type
Technical Report
Publication Date
Dec 07, 1992
Accession Number
ADA260047

Entities

People

  • David Siegmund

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Air Force Facilities
  • Algorithms
  • Boundaries
  • Change Detection
  • Clinical Trials
  • Crossings
  • Detection
  • Differential Geometry
  • Geometry
  • Probability
  • Random Walk
  • Regression Analysis
  • Scientific Research
  • Sequential Analysis
  • Stochastic Control

Fields of Study

  • Engineering

Readers

  • Statistical inference.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms