Robustness in statistical forecasting
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 predi...
Shranjeno v:
| Glavni avtor: | |
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| Format: | Livre numérique |
| Jezik: | Anglais |
| Izdano: |
Cham :
Springer International Publishing
2013.
Cham : Springer Nature |
| Online dostop: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Robustness in Statistical Forecasting, Texte imprimé, 9783319008417 • Robustness in Statistical Forecasting, Texte imprimé, 9783319345680 • Robustness in Statistical Forecasting, by Yuriy Kharin, Cham, Springer, 2013, 978-3-319-00839-4 |
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| 100 | 1 | |a Kharin, Yuriy. | |
| 245 | 1 | 0 | |a Robustness in statistical forecasting |c by Yuriy Kharin. |
| 260 | |a Cham : |b Springer International Publishing. | ||
| 260 | |a Cham : |b Springer Nature, |c 2013. | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 0 | |a Preface -- Symbols and Abbreviations -- Introduction -- A Decision-Theoretic Approach to Forecasting -- Time Series Models of Statistical Forecasting -- Performance and Robustness Characteristics in Statistical Forecasting -- Forecasting under Regression Models of Time Series -- Robustness of Time Series Forecasting Based on Regression Models -- Optimality and Robustness of ARIMA Forecasting -- Optimality and Robustness of Vector Autoregression Forecasting under Missing Values -- Robustness of Multivariate Time Series Forecasting Based on Systems of Simultaneous Equations -- Forecasting of Discrete Time Series -- Index. | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. chttps://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a 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. . | ||
| 776 | 0 | |t Robustness in Statistical Forecasting |b Texte imprimé |z 9783319008417 | |
| 776 | 0 | |t Robustness in Statistical Forecasting |b Texte imprimé |z 9783319345680 | |
| 776 | 0 | |0 174602510 |t Robustness in Statistical Forecasting |f by Yuriy Kharin |c Cham |n Springer |d 2013 |z 978-3-319-00839-4 | |
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