Iterative Procedures for Exact Maximum Likelihood Estimation in the First-Order Gaussian Moving Average Model

Abstract

Estimation of the parameters of a first-order Gaussian moving average model is treated in detail. Iterative methods in both the time and frequency domains are based on the maximization of the exact likelihood. Several methods for evaluating the necessary quadratic forms and traces are presented. The procedures are compared with other and with alternative procedures.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1990
Accession Number
ADA230812

Entities

People

  • R. P. Mentz
  • Theodore W. Anderson

Organizations

  • Stanford University

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Analysis Of Variance
  • Computations
  • Data Science
  • Equations
  • Frequency
  • Frequency Domain
  • Information Science
  • Linear Systems
  • Mathematical Filters
  • Maximum Likelihood Estimation
  • Polynomials
  • Probability
  • Random Variables
  • Statistical Algorithms
  • Statistical Analysis
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

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