Asymptotic Properties of Extended Yule-Walker Estimates of the AR Parameters of an ARMA (Autoregressive Moving-Average).

Abstract

The extended Yule-Walker equations are used to estimate the autoregressive parameters of an autoregressive moving-average time series. The asymptotic statistical properties of these estimates are derived. It is shown that they are asymptotically unbiased and normal; the covariance matrix of the limit distribution is calculated. The special case of estimating the autoregressive parameters of a noise corrupted autoregressive series is also treated. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 15, 1983
Accession Number
ADA134981

Entities

People

  • D. F. Gingras

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Classification
  • Covariance
  • Data Science
  • Distribution Functions
  • Equations
  • Gaussian Processes
  • Information Processing
  • Information Science
  • Military Research
  • Numbers
  • Probability
  • Sequences
  • Signal Processing
  • Stationary Processes
  • Statistics
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Statistical inference.