Wavelets in Functional Data Analysis (SpringerBriefs in Mathematics)
暫譯: 功能數據分析中的小波 (數學簡報系列)

Pedro A. Morettin, Aluísio Pinheiro, Brani Vidakovic

  • 出版商: Springer
  • 出版日期: 2017-11-23
  • 售價: $2,990
  • 貴賓價: 9.5$2,841
  • 語言: 英文
  • 頁數: 106
  • 裝訂: Paperback
  • ISBN: 3319596225
  • ISBN-13: 9783319596228
  • 相關分類: Data Science
  • 海外代購書籍(需單獨結帳)

商品描述

Wavelet-based procedures are key in many areas of statistics, applied mathematics, engineering, and science. This book presents wavelets in functional data analysis, offering a glimpse of problems in which they can be applied, including tumor analysis, functional magnetic resonance and meteorological data. Starting with the Haar wavelet, the authors explore myriad families of wavelets and how they can be used. High-dimensional data visualization (using Andrews' plots), wavelet shrinkage (a simple, yet powerful, procedure for nonparametric models) and a selection of estimation and testing techniques (including a discussion on Stein’s Paradox) make this a highly valuable resource for graduate students and experienced researchers alike.

商品描述(中文翻譯)

小波基礎的程序在統計學、應用數學、工程學和科學的許多領域中都是關鍵。本書介紹了小波在函數數據分析中的應用,提供了可以應用小波的問題的概覽,包括腫瘤分析、功能性磁共振成像和氣象數據。從Haar小波開始,作者探討了各種小波族及其使用方式。高維數據可視化(使用Andrews圖)、小波收縮(對於非參數模型的一種簡單而強大的程序)以及一系列估計和檢驗技術(包括對Stein悖論的討論)使本書成為研究生和經驗豐富的研究人員都非常有價值的資源。

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