| 书目名称 | Inference for Functional Data with Applications |
| 编辑 | Lajos Horváth,Piotr Kokoszka |
| 视频video | |
| 概述 | Definitive text for graduate or advanced undergraduate students seeking a self-contained introduction to the subject.Advanced researchers will benefit from novel asymptotic arguments.All procedures de |
| 丛书名称 | Springer Series in Statistics |
| 图书封面 |  |
| 描述 | .This book presents recently developed statistical methods and theory required for the application of the tools of functional data analysis to problems arising in geosciences, finance, economics and biology. It is concerned with inference based on second order statistics, especially those related to the functional principal component analysis. While it covers inference for independent and identically distributed functional data, its distinguishing feature is an in depth coverage of dependent functional data structures, including functional time series and spatially indexed functions. Specific inferential problems studied include two sample inference, change point analysis, tests for dependence in data and model residuals and functional prediction. All procedures are described algorithmically, illustrated on simulated and real data sets, and supported by a complete asymptotic theory. .The book can be read at two levels. Readers interested primarily in methodology will find detailed descriptions of the methods and examples of their application. Researchers interested also in mathematical foundations will find carefully developed theory. The organization of the chapters makes it easy |
| 出版日期 | Book 2012 |
| 关键词 | Asymptotic theory; Distributed functions; Functional data analysis; Functional time series; Hilbert spac |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4614-3655-3 |
| isbn_softcover | 978-1-4899-9052-5 |
| isbn_ebook | 978-1-4614-3655-3Series ISSN 0172-7397 Series E-ISSN 2197-568X |
| issn_series | 0172-7397 |
| copyright | Springer Science+Business Media New York 2012 |
发表于 2025-3-21 16:55:40
