Introduction to Functional Data Analysis
暫譯: 功能數據分析導論

Kokoszka, Piotr, Reimherr, Matthew

Introduction to Functional Data Analysis
  • 出版商: CRC
  • 出版日期: 2021-06-30
  • 售價: $2,350
  • 貴賓價: 9.5 折 $2,233
  • 語言: 英文
  • 頁數: 306
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1032096594
  • ISBN-13: 9781032096599
  • 相關分類: Data Science
  • 其他版本: Introduction to Functional Data Analysis

    • 立即出貨 (庫存=1)

相關主題

商品描述

Introduction to Functional Data Analysis provides a concise textbook introduction to the field. It explains how to analyze functional data, both at exploratory and inferential levels. It also provides a systematic and accessible exposition of the methodology and the required mathematical framework.

 

The book can be used as textbook for a semester-long course on FDA for advanced undergraduate or MS statistics majors, as well as for MS and PhD students in other disciplines, including applied mathematics, environmental science, public health, medical research, geophysical sciences and economics. It can also be used for self-study and as a reference for researchers in those fields who wish to acquire solid understanding of FDA methodology and practical guidance for its implementation. Each chapter contains plentiful examples of relevant R code and theoretical and data analytic problems.

 

The material of the book can be roughly divided into four parts of approximately equal length: 1) basic concepts and techniques of FDA, 2) functional regression models, 3) sparse and dependent functional data, and 4) introduction to the Hilbert space framework of FDA. The book assumes advanced undergraduate background in calculus, linear algebra, distributional probability theory, foundations of statistical inference, and some familiarity with R programming. Other required statistics background is provided in scalar settings before the related functional concepts are developed. Most chapters end with references to more advanced research for those who wish to gain a more in-depth understanding of a specific topic.

商品描述(中文翻譯)

《功能數據分析導論》提供了該領域的簡明教科書介紹。它解釋了如何在探索性和推論性層面上分析功能數據。書中還系統性且易於理解地闡述了方法論及所需的數學框架。

本書可用作高級本科生或碩士統計專業的學期課程教材，也適用於其他學科的碩士和博士生，包括應用數學、環境科學、公共衛生、醫學研究、地球物理科學和經濟學。它也可以用於自學，並作為這些領域研究人員的參考，幫助他們獲得對FDA方法論的扎實理解及其實施的實用指導。每章都包含大量相關的R程式碼示例以及理論和數據分析問題。

本書的內容大致可分為四個大致相等的部分：1) FDA的基本概念和技術，2) 功能回歸模型，3) 稀疏和依賴的功能數據，以及4) FDA的希爾伯特空間框架介紹。本書假設讀者具備高級本科的微積分、線性代數、分佈概率論、統計推斷基礎以及對R程式設計的某些熟悉程度。在發展相關的功能概念之前，還提供了其他所需的統計背景知識。大多數章節結尾都會參考更高級的研究，供希望深入了解特定主題的讀者參考。

作者簡介

Piotr Kokoszka is a professor of statistics at Colorado State University. His research interests include functional data analysis, with emphasis on dependent data structures, and applications to geosciences and finance. He is a coauthor of the monograph Inference for Functional Data with Applications (with L. Horváth). He is an associate editor of several journals, including Computational Statistics and Data Analysis, Journal of Multivariate Analysis, Journal of Time Series Analysis, and Scandinavian Journal of Statistics.

 

Matthew Reimherr is an assistant professor of statistics at Pennsylvania State University. His research interests include functional data analysis, with emphasis on longitudinal studies and applications to genetics and public health. He is an associate editor of Statistical Modeling.

作者簡介(中文翻譯)

Piotr Kokoszka 是科羅拉多州立大學的統計學教授。他的研究興趣包括功能數據分析，特別是依賴數據結構，以及在地球科學和金融領域的應用。他是專著 Inference for Functional Data with Applications（與 L. Horváth 共同撰寫）的合著者。他是多本期刊的副編輯，包括 Computational Statistics and Data Analysis、Journal of Multivariate Analysis、Journal of Time Series Analysis 和 Scandinavian Journal of Statistics。

 

Matthew Reimherr 是賓夕法尼亞州立大學的助理教授。他的研究興趣包括功能數據分析，特別是縱向研究及其在遺傳學和公共衛生中的應用。他是 Statistical Modeling 的副編輯。

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