Four options for modeling and forecasting time series data containing increasing seasonal variation are discussed, including data trans formations, double seasonal difference models and two kinds of transfer function-type ARIMA models employing seasonal dummy variables. An explanation is given for t
Forecasting time series with common seasonal patterns
β Scribed by John Geweke
- Publisher
- Elsevier Science
- Year
- 1993
- Tongue
- English
- Weight
- 107 KB
- Volume
- 55
- Category
- Article
- ISSN
- 0304-4076
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