Description: 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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EAN: 9783319345680
UPC: 9783319345680
ISBN: 9783319345680
MPN: N/A
Item Length: 23.4 cm
Item Height: 235 mm
Item Width: 155 mm
Author: Yuriy Kharin
Publication Name: Robustness in Statistical Forecasting
Format: Paperback
Language: English
Publisher: Springer International Publishing Ag
Subject: Engineering & Technology, Government, Mathematics
Publication Year: 2016
Type: Textbook
Item Weight: 5621 g
Number of Pages: 356 Pages
