Maximum Likelihood Estimation for an Autoregressive Process WITH Missing Observations,

Abstract

Three methods are proposed for estimation of the parameters of an autoregressive process of order p with missing observations. These methods are based on the maximum likelihood approach and use the EM algorithm, the Newton-Raphson method and the method of scoring, which are applied to the likelihood equations. Finally, comparison on those methods is also discussed. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1979
Accession Number
ADA076625

Entities

People

  • Suan-boon Tan

Organizations

  • University of Pittsburgh

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Covariance
  • Data Science
  • Equations
  • Information Science
  • Mathematics
  • Maximum Likelihood Estimation
  • Observation
  • Probability
  • Probability Density Functions
  • Random Variables
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Inference
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Radar Systems Engineering.