Nonparametric Functional Data Analysis: Theory and Practice (Springer Series in Statistics)

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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.

Author(s): Frédéric Ferraty, Philippe Vieu
Series: Springer Series in Statistics
Edition: 1
Publisher: Springer
Year: 2006

Language: English
Pages: 280