An Introduction to Applied Multivariate Analysis with R (2011) ( Use R! )

Brian Everitt

  • 出版商: Springer
  • 出版日期: 2011-05-03
  • 售價: $2,880
  • 貴賓價: 9.5$2,736
  • 語言: 英文
  • 頁數: 288
  • 裝訂: Paperback
  • ISBN: 1441996494
  • ISBN-13: 9781441996497
  • 相關分類: R 語言
  • 海外代購書籍(需單獨結帳)

買這商品的人也買了...

商品描述

The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos.

An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.

商品描述(中文翻譯)

研究人員在各個學科中收集的大多數數據集都是多變量的,這意味著在數據集中的每個單位上進行了多個測量、觀察或記錄。這些單位可能是人類受試者、考古文物、國家或其他各種事物。在少數情況下,將每個變量分離並單獨研究可能是合理的,但在大多數情況下,需要同時檢查所有變量,以充分理解數據的結構和關鍵特徵。為此,多變量分析的一種或另一種方法可能是有幫助的,這本書主要涉及這些方法。多變量分析包括用於描述和探索此類數據以及對其進行正式推論的方法。所有技術的目標通常是在噪聲存在的情況下顯示或提取數據中的信號,並在其明顯混亂中找出數據向我們展示的內容。

《應用多變量分析入門與R》探討了正確應用這些方法以從手頭的數據中提取盡可能多的信息,特別是以某種圖形表示形式,通過R軟件。在整本書中,作者提供了許多使用R代碼應用多變量技術於多變量數據的示例。