• DocumentCode
    851882
  • Title

    A necessary and sufficient condition for the existence of the maximum likelihood estimate in autoregressive models

  • Author

    Degerine, Serge

  • Author_Institution
    LMC, Univ. Joseph Fourier, Grenoble, France
  • Volume
    41
  • Issue
    2
  • fYear
    1993
  • fDate
    2/1/1993 12:00:00 AM
  • Firstpage
    988
  • Lastpage
    990
  • Abstract
    The author studies the existence of a maximum likelihood estimate (MLE) for the parameters of a pth-order autoregressive (AR) model from n⩾1 independent records of length m of a complex time series. It is shown that, for almost all such set of observations, the MLE exists if and only if the n records be exactly fitted by complex undamped sinusoids using the same set of p distinct frequencies
  • Keywords
    maximum likelihood estimation; signal processing; time series; AR model; MLE; autoregressive model; autoregressive models; complex time series; complex undamped sinusoids; frequencies; independent records; maximum likelihood estimate; necessary condition; signal processing; sufficient condition; Array signal processing; Correlation; Covariance matrix; Frequency; Linear systems; Maximum likelihood estimation; Parameter estimation; Relaxation methods; Signal processing; Sufficient conditions;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.193241
  • Filename
    193241