Data analysis and applications. 2, Utilization of results in Europe and other topics

Cover
Half-Title Page
Title Page
Copyright Page
Contents
Preface
Introduction: 50 Years of Data Analysis: From Exploratory Data Analysis to Predictive Modeling and Machine Learning
	I.1. The revolt against mathematical statistics
	I.2. EDA and unsupervised methods for dimension reduction
		I.2.1. The time of syntheses
		I.2.2. The time of clusterwise methods
		I.2.3. Extensions to new types of data
		I.2.4. Nonlinear data analysis
		I.2.5. The time of sparse methods
	I.3. Predictive modeling
		I.3.1. Paradigms and paradoxes
		I.3.2. From statistical learning theory to empirical validation
		I.3.3. Challenges
	I.4. Conclusion
	I.5. References
PART 1: Applications
1. Context-specific Independence in Innovation Study
	1.1. Introduction
	1.2. Parametrization for CS independencies
	1.3. Stratified chain graph models
	1.4. Application on real data
	1.5. Conclusion
	1.6. References
2. Analysis of the Determinants and Outputs of Innovation in the Nordic Countries
	2.1. Introduction
	2.2. Innovation
	2.3. Methodology
	2.4. Results
	2.5. Conclusion
	2.6. References
3. Bibliometric Variables Determining the Quality of a Dentistry Journal
	3.1. Introduction
	3.2. Statistical methodology
	3.3. Results
	3.4. Conclusions
	3.5. Acknowledgment
	3.6. References
4. Analysis of Dependence among Growth Rates of GDP of V4 Countries Using Four-dimensional Vine Copulas
	4.1. Introduction
	4.2. Theory
	4.3. Results
	4.4. Conclusion and future work
	4.5. Acknowledgment
	4.6. References
5. Monitoring the Compliance of Countries on Emissions Mitigation Using Dissimilarity Indices
	5.1. Introduction
	5.2. The proposed method
		5.2.1. Description of method for individual data
		5.2.2. Description of method for grouped data
	5.3. Application of method
		5.3.1. Application of method for individual data
		5.3.2. Application of method for grouped data
	5.4. Conclusions
	5.5. Appendix
	5.6. References
6. Maximum Entropy and Distributions of Five-Star Ratings
	6.1. Introduction
	6.2. Entropy framework to five-star ratings
	6.3. Maximum entropy of ratings for values k = 1,2,3,. . . ,30
		6.3.1. Ratings with two outcomes (k = 1)
		6.3.2. Ratings with three Outcomes (k=2)
		6.3.3. Ratings with four outcomes (k=3)
		6.3.4. Ratings with five outcomes (k = 4)
		6.3.5. Rating entropy for outcomes k>4
		6.3.6. Maximum entropy constraints for the binomial distribution
	6.4. Application to real five-star rating data
	6.5. Conclusions
	6.6. References
PART 2: The Impact of the Economic and Financial Crisis in Europe
7. Access to Credit for SMEs after the 2008 Financial Crisis: The Northern Italian Perspective
	7.1. Introduction
	7.2. Italian SMEs and access to credit
	7.3. The data
	7.4. Methodology
	7.5. Analysis and discussion
		7.5.1. The measure for the Great Recession period (2008–2012)
		7.5.2. The measure for the recovery period (2013–2015)
		7.5.3. Comparing the two crisis phases
	7.6. Conclusion
	7.7. References
8. Gender-Based Differences in the Impact of the Economic Crisis on Labor Market Flows in Southern Europe
	8.1. Introduction
	8.2. Data, methods and limitations
	8.3. Results
	8.4. Conclusions and discussion
	8.5. References
9. Measuring Labor Market Transition Probabilities in Europe with Evidence from the EU-SILC
	9.1. Introduction
	9.2. Data, methods and limitations
	9.3. Results
	9.4. Conclusions
	9.5. References
PART 3: Student Assessment and Employment in Europe
10. Almost Graduated, Close to Employment? Taking into Account the Characteristics of Companies Recruiting at a University Job Place Placement Office
	10.1. Introduction
	10.2. Recruiters and graduates seeking an HEI common ground
	10.3. Web survey pitfalls: considerations for data collection
	10.4. Sampled recruiters: an outline
	10.5. Conclusion
	10.6. References
11. How Variation of Scores of the Programme for International Student Assessment can be Explained through Analysis of Information
	11.1. Introduction
	11.2. Multiplicative models and Zighera’s parameterization
	11.3. Application to PISA surveys
		11.3.1. Data and variables
		11.3.2. Analysis of scores in mathematics
		11.3.3. Conclusion
	11.4. References
PART 4: Visualization
12. A Topological Discriminant Analysis
	12.1. Introduction
	12.2. Topological equivalence
	12.3. Topological discriminant analysis
	12.4. Application example
	12.5. Conclusion and perspectives
	12.6. Appendix
	12.7. References
13. Using Graph Partitioning to Calculate PageRank in a Changing Network
	13.1. Introduction
		13.1.1. Computing PageRank
	13.2. Changes in personalization vector
	13.3. Adding or removing edges between components
		13.3.1. Computations in practice
		13.3.2. Adding or removing an edge inside a component
		13.3.3. Maintaining the component structure
	13.4. Conclusions
	13.5. References
14. Visualizing the Political Spectrum of Germany by Contiguously Ordering the Party Policy Profiles
	14.1. Introduction
	14.2. The model
	14.3. Conclusions
	14.4. References
List of Authors
Index
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