• DocumentCode
    822103
  • Title

    Prediction error identification methods for stationary stochastic processes

  • Author

    Caines, P.E.

  • Author_Institution
    University of Toronto, Toronto, Ontario, Canada
  • Volume
    21
  • Issue
    4
  • fYear
    1976
  • fDate
    8/1/1976 12:00:00 AM
  • Firstpage
    500
  • Lastpage
    505
  • Abstract
    The strong consistency of a general class of prediction error identification methods for stationary stochastic processes is demonstrated. In particular, the strong consistency of the maximum likelihood method for stationary Gaussian processes [4], [5] and of the quadratic loss prediction error method for stationary stochastic processes [1]-[3] follow as special cases of the general result.
  • Keywords
    Parameter estimation; Prediction methods; Stochastic processes; maximum-likelihood (ML) estimation; Filters; Gaussian processes; Least squares methods; Linear systems; Maximum likelihood estimation; Minimization methods; Parameter estimation; Stochastic processes; Stochastic systems; Yield estimation;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.1976.1101304
  • Filename
    1101304
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=822103