Principal Component and Correspondence Analyses Using R
暫譯: 使用 R 進行主成分分析與對應分析

Abdi, Herve, Beaton, Derek

Principal Component and Correspondence Analyses Using R
  • 出版商: Springer
  • 出版日期: 2028-09-22
  • 售價: $1,980
  • 貴賓價: 9.5 折 $1,881
  • 語言: 英文
  • 頁數: 110
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3319092553
  • ISBN-13: 9783319092553

    • 尚未上市，無法訂購

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商品描述

With the right R packages, R is uniquely suited to perform Principal Component Analysis (PCA), Correspondence Analysis (CA), Multiple Correspondence Analysis (MCA), and metric multidimensional scaling (MMDS). The analyses depicted in this book use several packages specially developed for theses analyses and include (among others): the ExPosition suite, FactoMiner, ade4, and ca. The authors present each technique with one or several small examples that demonstrate how to enter the data, perform the standard analyses, and obtain professional quality graphics. Through explanations of the major options for how to carry out each method, readers can tailor the content of this book to their particular goals. Explanations include the effects of using particular packages. ExPosition is a great choice for the methods as it was written specifically for this book. However, options abound and are illustrated within unique scenarios. The first chapter includes installation of the packages. At the end of the book, a short appendix presents critical mathematical material for readers who want to go deeper into the theory.

商品描述(中文翻譯)

使用適當的 R 套件，R 特別適合執行主成分分析 (Principal Component Analysis, PCA)、對應分析 (Correspondence Analysis, CA)、多重對應分析 (Multiple Correspondence Analysis, MCA) 和度量多維縮放 (metric multidimensional scaling, MMDS)。本書中所描繪的分析使用了幾個專門為這些分析開發的套件，包括（但不限於）：ExPosition 套件、FactoMiner、ade4 和 ca。作者以一個或多個小範例介紹每種技術，展示如何輸入數據、執行標準分析並獲得專業品質的圖形。通過對每種方法的主要選項的解釋，讀者可以根據自己的特定目標調整本書的內容。解釋中包括使用特定套件的影響。ExPosition 是這些方法的絕佳選擇，因為它是專門為本書編寫的。然而，選項繁多，並在獨特的情境中進行說明。第一章包括套件的安裝。在書的末尾，附錄簡要介紹了對於希望深入理論的讀者來說至關重要的數學材料。

作者簡介

Hervé Abdi is currently a full professor in the School of Behavioral and Brain Sciences at the University of Texas at Dallas and is the author or co-author of more than 250 publications (including 12 books). His recent work is concerned with face and person perception, odor perception, and with computational modeling of these processes. He is also developing statistical techniques to analyze the structure of large data sets as found, for example, in Genomics, brain imaging, and sensory evaluation (e.g., principal component analysis, correspondence analysis, Partial Least Square methods, STATIS, DISTATIS, discriminant correspondence analysis, multiple factor analysis, multi-table analysis, and additive tree representations). He is co-author (with Derek Beaton) of several R packages implementing these techniques. He teaches or has taught classes in cognition, computational modeling, experimental design, multivariate statistics, and the analysis of brain imaging data.

Derek Beaton has a background in computer science and is currently working towards his PhD in Cognition and Neuroscience under his advisor, Dr. Hervé Abdi. Derek's interests are in developing new statistical approaches to better understand the contributions of genetics to brain and behavior. Recently, Derek was awarded a National Institutes of Health Ruth Kirschstein F31 fellowship via National Institute of Drug Abuse. His fellowship (co-sponsored by Drs. Hervé Abdi and Francesca Filbey) aims to reveal the genetic contributions to substance abuse and related traits. He is the main author of several R packages implementing the techniques described in this book.

作者簡介(中文翻譯)

Hervé Abdi 目前是德克薩斯州達拉斯大學行為與大腦科學學院的全職教授，並且是超過250篇出版物（包括12本書籍）的作者或合著者。他最近的研究關注於面孔和個體知覺、氣味知覺，以及這些過程的計算模型。他還在開發統計技術，以分析大型數據集的結構，例如在基因組學、腦成像和感官評估中（例如，主成分分析、對應分析、偏最小平方法、STATIS、DISTATIS、判別對應分析、多重因子分析、多表格分析和加法樹表示法）。他與Derek Beaton共同合著了幾個實現這些技術的R套件。他教授或曾教授認知、計算建模、實驗設計、多變量統計和腦成像數據分析等課程。

Derek Beaton 擁有計算機科學背景，目前在他的導師Hervé Abdi博士的指導下攻讀認知與神經科學的博士學位。Derek的興趣在於開發新的統計方法，以更好地理解遺傳對大腦和行為的貢獻。最近，Derek獲得了國立衛生研究院的Ruth Kirschstein F31獎學金，該獎學金由國立藥物濫用研究所提供。他的獎學金（由Hervé Abdi博士和Francesca Filbey博士共同贊助）旨在揭示遺傳對物質濫用及相關特徵的貢獻。他是幾個實現本書中描述技術的R套件的主要作者。

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