Sequential detection of a steady state

Moshe Pollak*, Tom Hope

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

ABSTRACT: In many contexts one observes a stochastic process with the goal of learning steady-state characteristics. Very often, a burn-in period is observed, at the end of which it is believed that steady state has been reached. The decision to halt and declare that the process is in steady-state is a sequential endeavor, based on the past-to-present observations, entailing continual decisions regarding whether steady state has already been attained. Usually, a rigorous statement of confidence/reliability of having reached steady-state that takes into account the sequential nature of the decision is not specified. The intention of this article is to present an approach to making a confidence statement of this nature. We focus on a sequence of independent observations that tends in a stochastically monotone fashion to a constant distribution. We also discuss a case of dependent observations.

Original languageAmerican English
Pages (from-to)2-29
Number of pages28
JournalSequential Analysis
Volume35
Issue number1
DOIs
StatePublished - 2 Jan 2016

Bibliographical note

Publisher Copyright:
© 2016, Copyright © Taylor & Francis Group, LLC.

Keywords

  • Changepoint
  • maximum likelihood
  • power one tests
  • sequential
  • statistical process control
  • steady state
  • tests of hypotheses

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