AR and ARMA spectral estimation

A. R. Rao, A. Durgunoglu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Autoregressive (AR) and Autoregressive-moving average (ARMA) methods of spectral analysis have been developed and are being increasingly used as alternatives to traditional methods of spectral analysis. Two of these methods developed by Marple and Friedlander are tested in this study by using generated data from models with known spectra. The Blackman-Tukey spectral estimates are also compared to the Marple and Friedlander estimates. The variability of the Marple and Friedlander estimates with sample sizes is investigated. Although both Marple's and Friedlander's methods are satisfactory, Friedlander's method is preferred because of its ability to handle a wider class of models.

Original languageEnglish (US)
Pages (from-to)35-50
Number of pages16
JournalStochastic Hydrology and Hydraulics
Issue number1
StatePublished - Mar 1 1988


  • Stochastic models
  • spectral analysis


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