• DocumentCode
    630722
  • Title

    Average run length function of CUSUM test with independent but non-stationary log-likelihood ratios

  • Author

    Yu Liu ; Li, X. Rong

  • Author_Institution
    Dept. of Electr. Eng., Univ. of New Orleans, New Orleans, LA, USA
  • fYear
    2013
  • fDate
    17-19 June 2013
  • Firstpage
    2803
  • Lastpage
    2808
  • Abstract
    The characteristics of Page´s CUSUM test are revealed by its average run length (ARL) function. It has been studied extensively under the assumption of independent and identically distributed (i.i.d.) log-likelihood ratios (LLR). In this case, it has been known that ARL is the solution of a Fredholm integral equation of the second kind (FIESK). However, few results are known when the LLR are independent but non-stationary (i.e., not identically distributed). This paper develops an inductive integral equation governing the ARL function in this setting. Unfortunately, in general it can not be solved analytically and the uniqueness of the solution is not guaranteed. However, for two frequently encountered cases-the LLR sequence converges in distribution and it has a periodic distribution, respectively-numerical solutions can be obtained by extending the system of linear algebraic equations method proposed for solving FIESK. Our solutions to these two special cases are compared with results of Monte Carlo simulations.
  • Keywords
    Fredholm integral equations; Monte Carlo methods; ARL function; CUSUM test; Fredholm integral equation; Monte Carlo simulations; average run length function; inductive integral equation; linear algebraic equations; nonstationary log likelihood ratios; numerical solution; periodic distribution; Approximation methods; Computational modeling; Equations; Mathematical model; Numerical models; Probability density function; CUSUM test; average run length; likelihood ratio; non-stationary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2013
  • Conference_Location
    Washington, DC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-0177-7
  • Type

    conf

  • DOI
    10.1109/ACC.2013.6580259
  • Filename
    6580259