| 书目名称 | Nonparametric Functional Data Analysis |
| 副标题 | Theory and Practice |
| 编辑 | Frédéric Ferraty,Philippe Vieu |
| 视频video | |
| 概述 | Shows how functional data can be studied through parameter-free statistical ideas.Offers an original presentation of new nonparametric statistical methods for functional data analysis.The text is care |
| 丛书名称 | Springer Series in Statistics |
| 图书封面 |  |
| 描述 | .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 |
| 出版日期 | Book 2006 |
| 关键词 | Parametric statistics; Pattern Recognition; calculus; data analysis; econometrics; modeling; nonparametric |
| 版次 | 1 |
| doi | https://doi.org/10.1007/0-387-36620-2 |
| isbn_softcover | 978-1-4419-2141-3 |
| isbn_ebook | 978-0-387-36620-3Series ISSN 0172-7397 Series E-ISSN 2197-568X |
| issn_series | 0172-7397 |
| copyright | Springer-Verlag New York 2006 |
发表于 2025-3-21 19:57:33
