The Asymptotic Distributions of Autoregressive Coefficients

Abstract

The asymptotic distribution of a finite set of autocorrelations is obtained for a time series from a linear stochastic process. The disturbances (or innovations) are martingale differences with bounded variances and bounded mixed fourth-order moments satisfying a uniform conditional square integrability condition. The conditions are weaker than those used previously for such asymptotic distributions. Specific topics include: autocorrelations, asymptotic distributions, martingale differences, bounded second order moments.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1991
Accession Number
ADA238538

Entities

People

  • Theodore W. Anderson

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Asymptotic Normality
  • Autocorrelation
  • Coefficients
  • Covariance
  • Data Science
  • Difference Equations
  • Information Science
  • Military Research
  • Normal Distribution
  • Probability
  • Random Variables
  • Regression Analysis
  • Stationary Processes
  • Statistical Algorithms
  • Statistics
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Fluid Dynamics.
  • Mathematical Modeling and Probability Theory.