9780387261423 - nonlinear time series: nonparametric and parametric methods (springer series in statistics) von fan, jianqing (3 Ergebnisse)
Sprache: Englisch
Verlag: Springer, 2005
Serie: Springer Series in Statistics, Buch 64 von 160. Buch 64 von 160 - Springer Series in Statistics
- Softcover
Anbieter: Anybook.com, Lincoln, Vereinigtes KönigreichAnybook.com
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht - Befriedigend
EUR 33,66
EUR 15,94 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 1 verfügbar
Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780387261423.
Sprache: Englisch
Verlag: Springer, 2005
Serie: Springer Series in Statistics, Buch 64 von 160. Buch 64 von 160 - Springer Series in Statistics
- Softcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 141,68
EUR 14,04 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. In English.
Sprache: Englisch
Verlag: Springer, Springer, 2005
Serie: Springer Series in Statistics, Buch 64 von 160. Buch 64 von 160 - Springer Series in Statistics
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 146,98
EUR 64,31 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Amongmanyexcitingdevelopmentsinstatisticsoverthelasttwodecades, nonlineartimeseriesanddata-analyticnonparametricmethodshavegreatly advanced along seemingly unrelated paths. In spite of the fact that the - plication of nonparametric techniques in time… series can be traced back to the 1940s at least, there still exists healthy and justi ed skepticism about the capability of nonparametric methods in time series analysis. As - thusiastic explorers of the modern nonparametric toolkit, we feel obliged to assemble together in one place the newly developed relevant techniques. Theaimofthisbookistoadvocatethosemodernnonparametrictechniques that have proven useful for analyzing real time series data, and to provoke further research in both methodology and theory for nonparametric time series analysis. Modern computers and the information age bring us opportunities with challenges. Technological inventions have led to the explosion in data c- lection (e.g., daily grocery sales, stock market trading, microarray data). The Internet makes big data warehouses readily accessible. Although cl- sic parametric models, which postulate global structures for underlying systems, are still very useful, large data sets prompt the search for more re nedstructures,whichleadstobetterunderstandingandapproximations of the real world. Beyond postulated parametric models, there are in nite other possibilities. Nonparametric techniques provide useful exploratory tools for this venture, including the suggestion of new parametric models and the validation of existing ones.
