A New Approach to ARMA Modeling.

Abstract

In recent years the Box-Jenkins method has become a popular technique for forecasting future behavior of a time series. Once the forecast model is known the method is very easy to employ and adequate computer packages are available for most purposes. Unfortunately the problem of determining the appropriate forecast model has, for models of any complexity, been one of the major stumbling blocks to the user of this method. In this paper a satisfactory solution to that problem is obtained and it is demonstrated by numerous examples how this greatly enlarges the class of data sets which can be adequately modeled by autoregressive-moving average models. This new approach is sufficiently unequivocal that most users will find it easy to implement. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1977
Accession Number
ADA047748

Entities

People

  • D. D. Mcintire
  • G. D. Kelley
  • H. L. Gray

Organizations

  • Southern Methodist University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Computers
  • Data Science
  • Data Sets
  • Difference Equations
  • Equations
  • Estimators
  • Frequency
  • Information Science
  • Noise
  • Plastic Explosives
  • Probability
  • Stationary
  • Statistical Algorithms
  • Statistics
  • Stochastic Processes
  • White Noise

Fields of Study

  • Computer science
  • Mathematics

Readers

  • Statistical inference.
  • Systems Analysis and Design