Forecasting with univariate Box-Jenkins models : concepts and cases

書誌事項

Forecasting with univariate Box-Jenkins models : concepts and cases

Alan Pankratz

(Wiley series in probability and mathematical statistics, . Applied probability and statistics)

Wiley, c1983

大学図書館所蔵 件 / 66

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

Explains the concepts and use of univariate Box-Jenkins/ARIMA analysis and forecasting through 15 case studies. Cases show how to build good ARIMA models in a step-by-step manner using real data. Also includes examples of model misspecification. Provides guidance to alternative models and discusses reasons for choosing one over another.

目次

BASIC CONCEPTS. Overview. Introduction to Box-Jenkins Analysis of a Single Data Series. Underlying Statistical Principles. An Introduction to the Practice of ARIMA Modeling. Notation and the Interpretation of ARIMA Models. Identification: Stationary Models. Identification: Nonstationary Models. Estimation. Diagnostic Checking. Forecasting. Seasonal and Other Periodic Models. THE ART OF ARIMA MODELING. Practical Rules. References. Index.

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