Modeling Seasonal ARMA Processes.

Abstract

Gray, Kelley, and McIntire (1978) have introduced a method, based on arrays of numbers called R- and S-arrays, for identifying p and q in an ARMA (p,q) process. In addition, they have illustrated how the same method is useful in detecting nonstationary factors in an observed process, and in suggesting an appropriate transformation to stationarity. In the present paper special attention is given to the problem of modeling seasonal ARMA processes using the S-array method. A general definition is given for a seasonal process, and the procedure for identifying and modeling such processes is discussed in detail. Additionally, an interesting theorem characterizing the S-arrays (based upon the sample autocorrelation) of seasonal processes is stated and a proof indicated. Finally, a data set (the international airline data) which exhibits the properties of a seasonal process is analyzed using the method discussed, and two models for the data are proposed. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1980
Accession Number
ADA091515

Entities

People

  • H. L. Gray
  • Jeffrey D. Hart

Organizations

  • Southern Methodist University

Tags

DTIC Thesaurus Topics

  • Autocorrelation
  • Coefficients
  • Data Sets
  • Difference Equations
  • Equations
  • Fourier Series
  • Frequency
  • Military Research
  • Reliability
  • Resonant Frequency
  • Standards
  • Stationary
  • Statistics
  • Time Series Analysis
  • United States
  • United States Government
  • Universities

Fields of Study

  • Mathematics

Readers

  • Statistical inference.