Statistical Learning and Modeling in Data Analysis: Methods and Applications (Studies in Classification, Data Analysis, and Knowledge Organization)

Preface
Contents
Interpreting Effects in Generalized Linear Modeling
	1 Introduction
	2 Interpreting Effects in Generalized Linear Models for Binary Data
		2.1 Alternatives to the Logit and Probit Links with Binary Responses
		2.2 Probability Effects Measures for Logistic Models
	3 Interpreting Effects in Models for Ordinal Responses
	4 Future Potential Research
	References
ACE, AVAS and Robust Data Transformations
	1 Introduction
	2 Extended Parametric Transformations
	3 Robustness and the Fan Plot
	4 Augmented Investment Fund Data
	5 Robust Analysis
	6 Nonparametric Transformations
	References
On Predicting Principal Components Through Linear Mixed Models
	1 Introduction
	2 Predictive Principal Components Analysis
	3 An Application to Some Well-Being Indicators
	4 Conclusions and Perspectives
	References
Robust Model-Based Learning to Discover New Wheat Varieties and Discriminate Adulterated Kernels in X-Ray Images
	1 Introduction and Motivation
	2 RAEDDA Model
		2.1 Transductive Learning
		2.2 Inductive Learning
	3 Anomaly and Novelty Detection in X-Ray Images of Wheat Kernels
	4 Conclusions
	References
A Dynamic Model for Ordinal Time Series: An Application to Consumers\' Perceptions of Inflation
	1 Introduction
	2 The Static CUB Model
	3 The Dynamic Model for Ordinal Time Series
	4 A Case Study: Consumer Inflation Perceptions
	5 Final Remarks
	References
Deep Learning to Jointly Analyze Images and Clinical Data for Disease Detection
	1 Introduction
	2 State of the Art and Challenges of the Medical Deep Learning
	3 Material and Methods
		3.1 The Data
		3.2 Previous Works on the Same Data
		3.3 The Model
	4 The Results
	5 Conclusions
	References
Studying Affiliation Networks Through Cluster CA and Blockmodeling
	1 Introduction
	2 Factorial Methods and Blockmodeling for Analyzing Affiliation Networks
	3 Applying Cluster CA and Blockmodeling to Affiliation Networks
	4 A Case Study of Stage Co-productions
		4.1 Comparison of Different Ways to Start Initial Cluster Allocation: Randomly and by Blockmodeling Positions
		4.2 Cluster CA for Affiliation Networks: Results From Random Start Clustering
	5 Concluding Remarks
	References
Sectioning Procedure on Geostatistical Indices Series of Pavement Road Profiles
	1 Introduction
	2 Geostatistical Tools for Road Pavement Characterization
	3 Brief Overview on Road Sectioning Methods
	4 Data Collection and Analysis
	5 Conclusion
	References
Directional Supervised Learning Through Depth Functions: An Application to ECG Waves Analysis
	1 Introduction and Motivations
	2 The Arrhythmia Data Set
		2.1 Previous Studies
		2.2 Scope of the Analysis and Variable Description
	3 Directional Depth-Based Supervised Learning Techniques
	4 Performance of Depth-Based Classifiers on ECG Waves
	5 Final Remarks
	References
Penalized Versus Constrained Approaches for Clusterwise Linear Regression Modeling
	1 Introduction
	2 The Methodology
		2.1 The Constrained Approach
		2.2 The Penalized Approach
		2.3 Selection of the Tuning Parameter
	3 Simulation Study
	4 Concluding Remarks
	References
Effect Measures for Group Comparisons in a Two-Component Mixture Model: A Cyber Risk Analysis
	1 Introduction
	2 cup Models
		2.1 Marginal Effect Measures for Covariates in cup Models
		2.2 Ordinal Superiority Measures in cup Models
	3 Example
	4 Discussion and Extension
	References
A Cramér–von Mises Test of Uniformity on the Hypersphere
	1 Introduction
	2 Background
		2.1 Testing Uniformity on Ωq
		2.2 Using Projections for Assessing Uniformity
		2.3 Projected Uniform Distribution
	3 A New Test of Uniformity
		3.1 Genesis of the Test Statistic
		3.2 U-statistic Form
		3.3 Asymptotic Distribution
	4 Numerical Experiments
	5 Are Venusian Craters Uniformly Distributed?
	References
On Mean And/or Variance Mixtures  of Normal Distributions
	1 Introduction
	2 Mean Mixture of Normal Distributions
		2.1 Properties
		2.2 Special Cases
	3 Mean–Variance Mixture of Normal Distributions
		3.1 Properties
		3.2 Special Cases
	4 Variance Mixture of Normal Distributions
		4.1 Properties
		4.2 Special Cases
	5 Parameter Estimation for MMN, MVMN, and VMN Distributions
	6 Conclusions
	References
Robust Depth-Based Inference  in Elliptical Models
	1 Depth and Illumination in Statistical Analysis
	2 Elliptically Symmetric Distributions
		2.1 Depth and Illumination of Elliptical Distributions
	3 Depth-Based Density Estimation
		3.1 The Density Generator as the Volume of Pδ
		3.2 The Density Generator as the Probability of Pδ
		3.3 Fisher Consistent Estimators of the Density
	4 Application
	References
Latent Class Analysis for the Derivation of Marketing Decisions: An Empirical Study for BEV Battery Manufacturers
	1 Motivation
	2 Latent Class Multinomial Logit Model
	3 Empirical Analysis
	4 Conclusion
	References
Small Area Estimation Diagnostics: The Case of the Fay–Herriot Model
	1 Introduction
	2 The Fay–Herriot Model
	3 Diagnostics for the Fay–Herriot Model
		3.1 The Leverage Matrix
		3.2 Influence on the MSE of the EBLUP
		3.3 Case Deletion Diagnostics and Cook\'s Distance
	4 An Application to Poverty Data
	5 Concluding Remarks
	References
A Comparison Between Methods to Cluster Mixed-Type Data: Gaussian Mixtures Versus Gower Distance
	1 Introduction
	2 The Model-Based Approach
		2.1 Classification, Model Selection, and Identifiability
	3 The Gower Distance Method
		3.1 k-means
		3.2 k-medoids
	4 Simulation Study
	5 Concluding Remarks
	References
Exploring the Gender Gap in Erasmus Student Mobility Flows
	1 Introduction
	2 Data and Methods
	3 Results
	References