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Exploratory multivariate analysis by...

Husson, François.

Exploratory multivariate analysis by example using R

Record Type:	Electronic resources : Monograph/item
Title/Author:	Exploratory multivariate analysis by example using RFrançois Husson, Sébastien Lê, Jérôme Pagès.
Author:	Husson, François.
other author:	Lê, Sébastien.
Published:	Boca Raton, FL :CRC Press, Taylor & Francis Group,c2017.
Description:	1 online resource (xiii, 248 p.) :ill.
Notes:	"A Chapman & Hall book"--title page.
Subject:	R (Computer program language)
Online resource:	https://www.taylorfrancis.com/books/9780429225437
ISBN:	9780429225437$q(electronic bk.)

Exploratory multivariate analysis by example using R
Husson, François.

Exploratory multivariate analysis by example using R[electronic resource] /François Husson, Sébastien Lê, Jérôme Pagès. - 2nd ed. - Boca Raton, FL :CRC Press, Taylor & Francis Group,c2017. - 1 online resource (xiii, 248 p.) :ill. - Chapman & Hall/CRC computer science and data analysis series. - Series in computer science and data analysis..

"A Chapman & Hall book"--title page.

Includes bibliographical references (p. 241-244) and index.

Cover ; Title Page ; Copyright Page ; Table of Contents ; Preface ; 1 : Principal Component Analysis (PCA) ; 1.1 Data -- Notation -- Examples ; 1.2 Objectives; 1.2.1 Studying Individuals ; 1.2.2 Studying Variables ; 1.2.3 Relationships between the Two Studies ; 1.3 Studying Individuals ; 1.3.1 The Cloud of Individuals ; 1.3.2 Fitting the Cloud of Individuals ; 1.3.2.1 Best Plane Representation of NI ; 1.3.2.2 Sequence of Axes for Representing NI ; 1.3.2.3 How Are the Components Obtained? ; 1.3.2.4 Example ; 1.3.3 Representation of the Variables as an Aid for Interpreting the Cloud of Individuals.

ISBN: 9780429225437$q(electronic bk.)Subjects--Topical Terms:

210846
R (Computer program language)

LC Class. No.: QA278 / .H87 2017

Dewey Class. No.: 519.5/3502855133

Exploratory multivariate analysis by example using R
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245 1 0 $a Exploratory multivariate analysis by example using R $h [electronic resource] / $c François Husson, Sébastien Lê, Jérôme Pagès.
250 $a 2nd ed.
260 $a Boca Raton, FL : $b CRC Press, Taylor & Francis Group, $c c2017.
300 $a 1 online resource (xiii, 248 p.) : $b ill.
490 1 $a Chapman & Hall/CRC computer science and data analysis series
500 $a "A Chapman & Hall book"--title page.
504 $a Includes bibliographical references (p. 241-244) and index.
505 0 $a Cover ; Title Page ; Copyright Page ; Table of Contents ; Preface ; 1 : Principal Component Analysis (PCA) ; 1.1 Data -- Notation -- Examples ; 1.2 Objectives; 1.2.1 Studying Individuals ; 1.2.2 Studying Variables ; 1.2.3 Relationships between the Two Studies ; 1.3 Studying Individuals ; 1.3.1 The Cloud of Individuals ; 1.3.2 Fitting the Cloud of Individuals ; 1.3.2.1 Best Plane Representation of NI ; 1.3.2.2 Sequence of Axes for Representing NI ; 1.3.2.3 How Are the Components Obtained? ; 1.3.2.4 Example ; 1.3.3 Representation of the Variables as an Aid for Interpreting the Cloud of Individuals.
505 8 $a 1.4 Studying Variables1.4.1 The Cloud of Variables; 1.4.2 Fitting the Cloud of Variables ; 1.5 Relationships between the Two Representations NI and NK ; 1.6 Interpreting the Data ; 1.6.1 Numerical Indicators ; 1.6.1.1 Percentage of Inertia Associated with a Component ; 1.6.1.2 Quality of Representation of an Individual or Variable ; 1.6.1.3 Detecting Outliers ; 1.6.1.4 Contribution of an Individual or Variable to the Construction of a Component ; 1.6.2 Supplementary Elements ; 1.6.2.1 Representing Supplementary Quantitative Variables ; 1.6.2.2 Representing Supplementary Categorical Variables.
505 8 $a 1.6.2.3 Representing Supplementary Individuals1.6.3 Automatic Description of the Components ; 1.7 Implementation with FactoMineR ; 1.8 Additional Results ; 1.8.1 Testing the Significance of the Components ; 1.8.2 Variables : Loadings versus Correlations ; 1.8.3 Simultaneous Representation: Biplots; 1.8.4 Missing Values; 1.8.5 Large Datasets; 1.8.6 Varimax Rotation ; 1.9 Example : The Decathlon Dataset ; 1.9.1 Data Description -- Issues ; 1.9.2 Analysis Parameters ; 1.9.2.1 Choice of Active Elements ; 1.9.2.2 Should the Variables Be Standardised? ; 1.9.3 Implementation of the Analysis.
505 8 $a 1.9.3.1 Choosing the Number of Dimensions to Examine 1.9.3.2 Studying the Cloud of Individuals ; 1.9.3.3 Studying the Cloud of Variables ; 1.9.3.4 Joint Analysis of the Cloud of Individuals and the Cloud of Variables ; 1.9.3.5 Comments on the Data; 1.10 Example : The Temperature Dataset ; 1.10.1 Data Description -- Issues ; 1.10.2 Analysis Parameters ; 1.10.2.1 Choice of Active Elements ; 1.10.2.2 Should the Variables Be Standardised? ; 1.10.3 Implementation of the Analysis ; 1.11 Example of Genomic Data : The Chicken Dataset ; 1.11.1 Data Description -- Issues ; 1.11.2 Analysis Parameters.
505 8 $a 1.11.3 Implementation of the Analysis2: Correspondence Analysis (CA) ; 2.1 Data -- Notation -- Examples ; 2.2 Objectives and the Independence Model ; 2.2.1 Objectives ; 2.2.2 Independence Model and X2 Test ; 2.2.3 The Independence Model and CA ; 2.3 Fitting the Clouds ; 2.3.1 Clouds of Row Profiles ; 2.3.2 Clouds of Column Profiles ; 2.3.3 Fitting Clouds NI and NJ ; 2.3.4 Example : Women's Attitudes to Women's Work in France in 1970 ; 2.3.4.1 Column Representation (Mother's Activity) ; 2.3.4.2 Row Representation (Partner's Work) ; 2.3.5 Superimposed Representation of Both Rows and Columns.
588 $a Print version record.
650 0 $a R (Computer program language) $3 210846
650 0 $a Multivariate analysis. $3 181905
700 1 $a Lê, Sébastien. $3 507090
700 1 $a Pagès, Jérôme. $3 507091
830 0 $a Series in computer science and data analysis. $3 378361
856 4 0 $u https://www.taylorfrancis.com/books/9780429225437