The Estimation of Time Series Models. Part I. Yet another Algorithm for the Exact Likelihood of ARMA (Autoregressive-Moving Average) Models.

Abstract

This paper presents a method for calculating the likelihood function of autoregressive-moving average (ARMA) models for time series data. Model estimation requires maximization of the likelihood, and to assist in this, a method for calculating derivatives of the function is also presented. The computational efficiency is competitive with that of other algorithms for this purpose. Extensions which allow for seasonal models, missing data, and the estimation of a data transformation are also described. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1983
Accession Number
ADA130500

Entities

People

  • G. Tunnicliffe-wilson

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Coefficients
  • Computations
  • Data Science
  • Efficiency
  • Engineering
  • Equations
  • Estimators
  • Information Science
  • Kalman Filters
  • Mathematical Analysis
  • Mathematics
  • Probability
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Statistical inference.