التفاصيل البيبلوغرافية
| العنوان: |
Prediction-based adaptive compositional model for seasonal time series analysis. |
| المؤلفون: |
Chang, Kun, Chen, Rong, Fomby, Thomas B. |
| المصدر: |
Journal of Forecasting; Nov2017, Vol. 36 Issue 7, p842-853, 12p |
| مصطلحات موضوعية: |
BUSINESS forecasting, TIME series analysis, DISTRIBUTION (Economic theory), ESTIMATION theory, COMPUTER simulation |
| مستخلص: |
In this paper we propose a new class of seasonal time series models, based on a stable seasonal composition assumption. With the objective of forecasting the sum of the next ℓ observations, the concept of rolling season is adopted and a structure of rolling conditional distributions is formulated. The probabilistic properties, estimation and prediction procedures, and the forecasting performance of the model are studied and demonstrated with simulations and real examples. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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