Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data explo… Mehr…
Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This book links these two fields of modern statistics by explaining how functional data can be studied through parameter-free statistical ideas. This book starts from theoretical foundations including functional nonparametric modeling, description of the mathematical framework, construction of the statistical methods, and statements of their asymptotic behaviors. It proceeds to computational issues including R and S-PLUS routines. Several functional datasets in chemometrics, econometrics, and pattern recognition are used to emphasize the wide scope of nonparametric functional data analysis in applied sciences. The companion Web site includes R and S-PLUS routines, command lines for reproducing examples presented in the book, and the functional datasets. Rather than set application against theory, this book is really an interface of these two features of statistics. A special effort has been made in writing this book to accommodate several levels of reading. The computational aspects are oriented toward practitioners whereas open problems emerging from this new field of statistics will attract Ph.D. students and academic researchers. Finally, this book is also accessible to graduate students starting in the area of functional statistics., Springer<
Springer.com
Nr. 978-0-387-30369-7. Versandkosten:Worldwide free shipping, , plus shipping costs. (EUR 0.00) Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data explo… Mehr…
Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This book links these two fields of modern statistics by explaining how functional data can be studied through parameter-free statistical ideas. At the same time it shows how functional data can be studied through parameter-free statistical ideas, and offers an original presentation of new nonparametric statistical methods for functional data analysis. New Textbooks>Hardcover>Science>Statistics & Probability>Statistics & Probability, Springer New York Core >2 >T<
BarnesandNoble.com
new in stock. Versandkosten:plus shipping costs., zzgl. Versandkosten Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
*Nonparametric Functional Data Analysis: Theory and Practice* - Models Theory Applications and Implementations. Auflage 2006 / gebundene Ausgabe für 151.49 € / Aus dem Bereich: Bücher, Ra… Mehr…
*Nonparametric Functional Data Analysis: Theory and Practice* - Models Theory Applications and Implementations. Auflage 2006 / gebundene Ausgabe für 151.49 € / Aus dem Bereich: Bücher, Ratgeber, Computer & Internet Medien > Bücher nein Buch (gebunden) Hardcover;Naturwissenschaften, Medizin, Informatik, Technik;Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik, SPRINGER NATURE<
Hugendubel.de
Versandkosten:Shipping in 2 weeks, , Versandkostenfrei nach Hause oder Express-Lieferung in Ihre Buchhandlung., DE. (EUR 0.00) Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data explo… Mehr…
Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This book links these two fields of modern statistics by explaining how functional data can be studied through parameter-free statistical ideas. This book starts from theoretical foundations including functional nonparametric modeling, description of the mathematical framework, construction of the statistical methods, and statements of their asymptotic behaviors. It proceeds to computational issues including R and S-PLUS routines. Several functional datasets in chemometrics, econometrics, and pattern recognition are used to emphasize the wide scope of nonparametric functional data analysis in applied sciences. The companion Web site includes R and S-PLUS routines, command lines for reproducing examples presented in the book, and the functional datasets. Rather than set application against theory, this book is really an interface of these two features of statistics. A special effort has been made in writing this book to accommodate several levels of reading. The computational aspects are oriented toward practitioners whereas open problems emerging from this new field of statistics will attract Ph.D. students and academic researchers. Finally, this book is also accessible to graduate students starting in the area of functional statistics., Springer<
Nr. 978-0-387-30369-7. Versandkosten:Worldwide free shipping, , plus shipping costs. (EUR 0.00)
Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data explo… Mehr…
Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This book links these two fields of modern statistics by explaining how functional data can be studied through parameter-free statistical ideas. At the same time it shows how functional data can be studied through parameter-free statistical ideas, and offers an original presentation of new nonparametric statistical methods for functional data analysis. New Textbooks>Hardcover>Science>Statistics & Probability>Statistics & Probability, Springer New York Core >2 >T<
new in stock. Versandkosten:plus shipping costs., zzgl. Versandkosten
*Nonparametric Functional Data Analysis: Theory and Practice* - Models Theory Applications and Implementations. Auflage 2006 / gebundene Ausgabe für 151.49 € / Aus dem Bereich: Bücher, Ra… Mehr…
*Nonparametric Functional Data Analysis: Theory and Practice* - Models Theory Applications and Implementations. Auflage 2006 / gebundene Ausgabe für 151.49 € / Aus dem Bereich: Bücher, Ratgeber, Computer & Internet Medien > Bücher nein Buch (gebunden) Hardcover;Naturwissenschaften, Medizin, Informatik, Technik;Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik, SPRINGER NATURE<
Versandkosten:Shipping in 2 weeks, , Versandkostenfrei nach Hause oder Express-Lieferung in Ihre Buchhandlung., DE. (EUR 0.00)
1Da einige Plattformen keine Versandkonditionen übermitteln und diese vom Lieferland, dem Einkaufspreis, dem Gewicht und der Größe des Artikels, einer möglichen Mitgliedschaft der Plattform, einer direkten Lieferung durch die Plattform oder über einen Drittanbieter (Marketplace), etc. abhängig sein können, ist es möglich, dass die von eurobuch angegebenen Versandkosten nicht mit denen der anbietenden Plattform übereinstimmen.
Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This book links these two fields of modern statistics by explaining how functional data can be studied through parameter-free statistical ideas. At the same time it shows how functional data can be studied through parameter-free statistical ideas, and offers an original presentation of new nonparametric statistical methods for functional data analysis.
Detailangaben zum Buch - Nonparametric Functional Data Analysis: Theory and Practice Frïdïric Ferraty Author
EAN (ISBN-13): 9780387303697 ISBN (ISBN-10): 0387303693 Gebundene Ausgabe Taschenbuch Erscheinungsjahr: 2006 Herausgeber: Springer New York Core >2 >T 268 Seiten Gewicht: 0,531 kg Sprache: eng/Englisch
Buch in der Datenbank seit 2007-06-13T07:56:16+02:00 (Berlin) Detailseite zuletzt geändert am 2023-10-27T20:27:18+02:00 (Berlin) ISBN/EAN: 0387303693
ISBN - alternative Schreibweisen: 0-387-30369-3, 978-0-387-30369-7 Alternative Schreibweisen und verwandte Suchbegriffe: Autor des Buches: ric, philippe, frédéric, philipp springer, frederic Titel des Buches: theory data, nonparametric functional data analysis, func, edition, springer series
Daten vom Verlag:
Autor/in: Frédéric Ferraty Titel: Springer Series in Statistics; Nonparametric Functional Data Analysis - Theory and Practice Verlag: Springer; Springer US 260 Seiten Erscheinungsjahr: 2006-06-06 New York; NY; US Sprache: Englisch 142,99 € (DE)
BB; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Parametric statistics; Pattern Recognition; calculus; data analysis; econometrics; modeling; nonparametric methods; statistical method; statistics; Probability Theory; Statistical Theory and Methods; Econometrics; Mathematical Applications in Environmental Science; Earth Sciences; Probability and Statistics in Computer Science; Stochastik; Ökonometrie und Wirtschaftsstatistik; Umwelt; Angewandte Mathematik; Geowissenschaften; Mathematik für Informatiker; EA; BC
Statistical Background for Nonparametric Statistics and Functional Data.- to Functional Nonparametric Statistics.- Some Functional Datasets and Associated Statistical Problematics.- What is a Well-Adapted Space for Functional Data?.- Local Weighting of Functional Variables.- Nonparametric Prediction from Functional Data.- Functional Nonparametric Prediction Methodologies.- Some Selected Asymptotics.- Computational Issues.- Nonparametric Classification of Functional Data.- Functional Nonparametric Supervised Classification.- Functional Nonparametric Unsupervised Classification.- Nonparametric Methods for Dependent Functional Data.- Mixing, Nonparametric and Functional Statistics.- Some Selected Asymptotics.- Application to Continuous Time Processes Prediction.- Conclusions.- Small Ball Probabilities and Semi-metrics.- Some Perspectives.
Weitere, andere Bücher, die diesem Buch sehr ähnlich sein könnten:
