Overview
- The first book with a specific focus on robustness of time series forecasting
- Evaluates sensitivity of the forecast risks to distortions and presents new robust forecasting procedures
- Presentation of the material follows the pattern “model ? method ? algorithm ? computation results based on simulated / real-world data” ?
- Includes supplementary material: sn.pub/extras
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Table of contents (10 chapters)
Keywords
About this book
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.
Reviews
From the reviews:
“The book is intended for mathematicians, statisticians and software developers in applied mathematics, computer science, data analysis, and econometrics, among other topics. It is a good text for advanced undergraduate and postgraduate students of the mentioned disciplines.” (Oscar Bustos, zbMATH, Vol. 1281, 2014)
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Robustness in Statistical Forecasting
Authors: Yuriy Kharin
DOI: https://doi.org/10.1007/978-3-319-00840-0
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2013
Hardcover ISBN: 978-3-319-00839-4Published: 17 September 2013
Softcover ISBN: 978-3-319-34568-0Published: 23 August 2016
eBook ISBN: 978-3-319-00840-0Published: 04 September 2013
Edition Number: 1
Number of Pages: XVI, 356
Number of Illustrations: 47 b/w illustrations
Topics: Statistical Theory and Methods, Probability Theory and Stochastic Processes, Statistics for Business, Management, Economics, Finance, Insurance, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Mathematical and Computational Engineering