• DocumentCode
    1657095
  • Title

    Structural breaks estimation for long memory signals

  • Author

    Song, Li ; Bondon, Pascal

  • Author_Institution
    CNRS, Univ. Paris-Sud, Gif-sur-Yvette, France
  • fYear
    2009
  • Firstpage
    237
  • Lastpage
    240
  • Abstract
    We consider the problem of estimating the structural breaks in a long memory FARIMA process. The number m of break points as well as their locations, the order (p, d, q) and the parameters of each regime are assumed to be unknown. To estimate the unknown parameters, we propose two criteria based on the minimum description length (MDL) principle of Rissanen, namely a direct extension of MDL and an improved MDL criterion embedded with Bayes information criterion (BIC). A genetic algorithm is implemented to optimize these two criteria. Monte Carlo simulation results show that both criteria perform well for estimating the break points number and their locations. The direct extension of MDL tends to over-estimate the regimes model order which is not the case of the improved MDL criterion.
  • Keywords
    Bayes methods; Monte Carlo methods; estimation theory; genetic algorithms; signal processing; Bayes information criterion; Monte Carlo simulation; Rissanen principle; genetic algorithm; long memory FARIMA process; long memory signals; minimum description length; structural break estimation; Bonding; Difference equations; Electronic equipment testing; Genetic algorithms; Hydrology; Meteorology; Parameter estimation; Signal processing; Statistical analysis; Yttrium; Long memory; MDL; Piecewise FARIMA model; Structural breaks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on
  • Conference_Location
    Cardiff
  • Print_ISBN
    978-1-4244-2709-3
  • Electronic_ISBN
    978-1-4244-2711-6
  • Type

    conf

  • DOI
    10.1109/SSP.2009.5278596
  • Filename
    5278596