Time Series Forecasting by ARARMA Models.

Abstract

The relation between various basic problems of time series analysis is presented. Exponential smoothing methods are developed from the point of view prediction theory and extended. ARARMA models are introduced. Methods of ARARMA model fitting are outlined. Since 'the proof of the pudding is in the eating,' the methods proposed are illustrated using some classic examples of time series, including international airline passengers, Makridakis metals series and sunspots.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1980
Accession Number
ADA094409

Entities

People

  • Emanuel Parzen

Organizations

  • Texas A&M University

Tags

DTIC Thesaurus Topics

  • Computing-Related Activities
  • Data Science
  • Delphi Method
  • Information Science
  • Interdisciplinary Science
  • Mathematics
  • Passengers
  • Plastic Explosives
  • Statistical Analysis
  • Statistics
  • Time Series Analysis

Fields of Study

  • Mathematics

Readers

  • Statistical inference.