Maximum Likelihood Estimation of Vector Autoregressive Moving Average Models.

Abstract

A method is presented for the estimation of the parameters in the vector autoregressive moving average time series model. The estimation procedure is derived from the maximum likelihood approach and is based on Newton-Raphson techniques applied to the likelihood equations. The resulting two-step Newton-Raphson procedure is computationally simple, involving only generalized least squares estimation in the second step. This Newton-Raphson estimator is shown to be asymptotically efficient and to possess a limiting multivariate normal distribution. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1976
Accession Number
ADA031116

Entities

People

  • Greg Reinsel

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Computations
  • Computer Programs
  • Computers
  • Covariance
  • Digital Computers
  • Equations
  • Estimators
  • Maximum Likelihood Estimation
  • Military Research
  • New York
  • Normal Distribution
  • Probability
  • Simultaneous Equations
  • Statistics
  • Time Series Analysis
  • United States
  • United States Government

Fields of Study

  • Mathematics

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Regression Analysis.