Exploratory Multivariate Analysis by Example using R

Content: 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 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 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 1.9.3.1 Choosing the Number of Dimensions to Examine1.9.3.2 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 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