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Añadir al carritoCondición: New. In.
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Añadir al carritoPaperback. Condición: New.
Librería: Books Puddle, New York, NY, Estados Unidos de America
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Añadir al carritoCondición: New. pp. 372 Softcover reprint of the original 1st ed. 2013 edition NO-PA16APR2015-KAP.
Idioma: Inglés
Publicado por Springer International Publishing, 2016
ISBN 10: 3319345680 ISBN 13: 9783319345680
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 53,49
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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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Añadir al carritoPaperback. Condición: Brand New. reprint edition. 372 pages. 9.30x6.20x0.84 inches. In Stock.
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Añadir al carritoTaschenbuch. Condición: Neu. Robustness in Statistical Forecasting | Yuriy Kharin | Taschenbuch | xvi | Englisch | 2016 | Springer | EAN 9783319345680 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Publicado por Springer International Publishing Aug 2016, 2016
ISBN 10: 3319345680 ISBN 13: 9783319345680
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 53,49
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book offers solutions to such topical problems as developing mathematical models and descriptions of typical distortions in applied forecasting problems; evaluating robustness for traditional forecasting procedures under distortionism and more. 372 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 71,07
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Añadir al carritoCondición: New. Print on Demand pp. 372.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 77,52
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 372.
Idioma: Inglés
Publicado por Springer International Publishing, 2016
ISBN 10: 3319345680 ISBN 13: 9783319345680
Librería: moluna, Greven, Alemania
EUR 48,37
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 .
Idioma: Inglés
Publicado por Springer, Palgrave Macmillan Aug 2016, 2016
ISBN 10: 3319345680 ISBN 13: 9783319345680
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 53,49
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 372 pp. Englisch.