Robustness in Statistical Forecasting
Kharin, Yuriy
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Add to basketSold by Books Puddle, New York, NY, U.S.A.
AbeBooks Seller since November 22, 2018
Condition: New
Quantity: 4 available
Add to basketpp. 372 Softcover reprint of the original 1st ed. 2013 edition NO-PA16APR2015-KAP.
Seller Inventory # 26378097557
Traditional procedures in the statistical forecasting of time series, which are proved to be optimal under the hypothetical model, are often not robust under relatively small distortions (misspecification, outliers, missing values, etc.), leading to actual forecast risks (mean square errors of prediction) that are much higher than the theoretical values. This monograph fills a gap in the literature on robustness in statistical forecasting, offering solutions to the following topical problems:
- developing mathematical models and descriptions of typical distortions in applied forecasting problems;
- evaluating the robustness for traditional forecasting procedures under distortions;
- obtaining the maximal distortion levels that allow the “safe” use of the traditional forecasting algorithms;
- creating new robust forecasting procedures to arrive at risks that are less sensitive to definite distortion types.
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