Existence of Maximum Likelihood Estimators of Autoregressive and Moving Average Models.

Abstract

There is given a sufficient condition on the observations from a scalar autoregressive process such that the maximum likelihood estimate exists and corresponds to a stationary process. A sufficient condition is given for the likelihood function to fail to have a maximum. In a moving average model the maximum likelihood estimates always exist. Some results are obtained for the autoregressive moving average model and vector models. It is shown that the solution to the sample Yule-Walker equations in the autoregressive case yield a stationary process. (Author)

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1980
Accession Number
ADA096995

Entities

People

  • Raul P. Mentz
  • Theodore W. Anderson

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Data Science
  • Equations
  • Estimators
  • Information Science
  • Mathematics
  • Observation
  • Stationary
  • Stationary Processes
  • Statistical Algorithms
  • Statistical Analysis

Fields of Study

  • Mathematics

Readers

  • Statistical inference.