Asymptotic Normality of Autoregressive Parameter Estimates for Mixed Time Series

Abstract

In this report it is shown for mixed time series, a series generated by an autoregressive moving-average (ARMA) process or by an autoregressive process observed in additive white noise (AR+N), that estimates of the autogressive (AR) parameters are asymptotically multivariate jointly normal with zero mean and finite covariance matrix. The structure of the asymptotic covariance matrix is evaluated for both types of mixed time series. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1981
Accession Number
ADA108781

Entities

People

  • D. F. Gingras

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Additives (Chemicals)
  • Asymptotic Normality
  • Classification
  • Covariance
  • Data Science
  • Equations
  • Estimators
  • Information Science
  • Noise
  • Normality
  • Probability
  • Random Variables
  • Statistical Analysis
  • Statistics
  • Test And Evaluation
  • Time Series Analysis
  • White Noise

Fields of Study

  • Mathematics

Readers

  • Statistical inference.