Statistical Analysis of Autoregressive Spectral Estimates for Noise Corrupted Autoregressive Series.

Abstract

Estimation of the spectral density function for a gaussian distributed autoregressive series from observations of a noise corrupted version is considered when the order of the autoregressive series is assumed to be known. When the high-order Yule-Walker equation estimates of the autoregressive parameters are used to form the spectral density estimate, it is shown that the estimate is weakly consistent and asymptotically normal with zero mean and finite variance. A closed form expression for the asymptotic variance is developed and the expression is analyzed for the first-order AR series case. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1984
Accession Number
ADA149543

Entities

People

  • D. F. Gingras

Tags

Communities of Interest

  • Air Platforms
  • C4I

DTIC Thesaurus Topics

  • Covariance
  • Data Science
  • Equations
  • Frequency
  • Information Science
  • Military Research
  • Noise
  • Observation
  • Power Spectra
  • Probability
  • Random Variables
  • Security
  • Signal Processing
  • Stationary
  • Statistical Analysis
  • Statistical Inference
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Statistical inference.