• DocumentCode
    2403815
  • Title

    Applications of stochastic complexity and related computational experiments

  • Author

    Baikovicius, Jimmy ; Gerencsér, László

  • Author_Institution
    Dept. of Electr. Eng., McGill Univ., Montreal, Que., Canada
  • fYear
    1992
  • fDate
    1992
  • Firstpage
    3311
  • Abstract
    The authors show how to solve model selection and change-point detection problems for ARMA processes in real time, using a form of predictive stochastic complexity. The effect of parameter uncertainty versus model order uncertainty is presented. The proposed solutions are illustrated by means of computer simulations
  • Keywords
    modelling; statistical analysis; time series; ARMA processes; change-point detection; computational experiments; model order uncertainty; model selection; parameter uncertainty; predictive stochastic complexity; Algebra; Automation; Computer simulation; Difference equations; Particle measurements; Polynomials; Predictive models; Stochastic processes; Uncertain systems; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
  • Conference_Location
    Tucson, AZ
  • Print_ISBN
    0-7803-0872-7
  • Type

    conf

  • DOI
    10.1109/CDC.1992.371025
  • Filename
    371025