Data Analysis and Applications 2

Christos H. Skiadas is the Founder and former Director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete, Greece. He continues his work at the university at the ManLab in the Department of Production Engineering and Management.James R. Bozeman holds a PhD in Mathematics from Dartmouth College, USA, and is Professor of Mathematics at the American University of Malta.

• Preface xiIntroduction xiiiGilbert SAPORTAPart 1 Applications 1Chapter 1 Context-specific Independence in Innovation Study 3Federica NICOLUSSI and Manuela CAZZARO1.1 Introduction 31.2 Parametrization for CS independencies 41.3 Stratified chain graph models 61.4 Application on real data 71.5 Conclusion 121.6 References 12Chapter 2 Analysis of the Determinants and Outputs of Innovation in the Nordic Countries 15Cátia ROSÁRIO, António Augusto COSTA and Ana LORGA DA SILVA2.1 Introduction 152.2 Innovation 162.3 Methodology 192.4 Results 212.5 Conclusion 252.6 References 26Chapter 3 Bibliometric Variables Determining the Quality of a Dentistry Journal 29Pilar VALDERRAMA, Manuel ESCABIAS, Evaristo JIMÉNEZ-CONTRERAS, Mariano JVALDERRAMA and Pilar BACA3.1 Introduction 293.2 Statistical methodology 303.3 Results 323.4 Conclusions 353.5 Acknowledgment 353.6 References 36Chapter 4 Analysis of Dependence among Growth Rates of GDP of V4 Countries Using Four-dimensional Vine Copulas 37Jozef KOMORNÍK, Magda KOMORNÍKOVÁ and Tomáš BACIGÁL4.1 Introduction 374.2 Theory 384.3 Results 424.4 Conclusion and future work 454.5 Acknowledgment 474.6 References 47Chapter 5 Monitoring the Compliance of Countries on Emissions Mitigation Using Dissimilarity Indices 49Eleni KETZAKI, Stavros RALLAKIS, Nikolaos FARMAKIS and Eftichios SARTZETAKIS5.1 Introduction 495.2 The proposed method 505.2.1 Description of method for individual data 515.2.2 Description of method for grouped data 525.3 Application of method 535.3.1 Application of method for individual data 545.3.2 Application of method for grouped data 555.4 Conclusions 555.5 Appendix 575.6 References 58Chapter 6 Maximum Entropy and Distributions of Five-Star Ratings 59Yiannis DIMOTIKALIS6.1 Introduction 596.2 Entropy framework to five-star ratings 606.3 Maximum entropy of ratings for values k = 1,2,3,,30 666.3.1 Ratings with two outcomes (k = 1) 666.3.2 Ratings with three Outcomes (k=2) 696.3.3 Ratings with four outcomes (k=3) 736.3.4 Ratings with five outcomes (k = 4) 766.3.5 Ratings entropy for outcomes k>4 806.3.6 Maximum entropy constraints for the binomial distribution 826.4 Application to real five-star rating data 836.5 Conclusions 866.6 References 86Part 2 The Impact of the Economic and Financial Crisis in Europe 89Chapter 7 Access to Credit for SMEs after the 2008 Financial Crisis: The Northern Italian Perspective 91Cinzia COLAPINTO and Mariangela ZENGA7.1 Introduction 917.2 Italian SMEs and access to credit 927.3 The data 937.4 Methodology 947.5 Analysis and discussion 977.5.1 The measure for the Great Recession period (2008–2012) 977.5.2 The measure for the recovery period (2013–2015) 997.5.3 Comparing the two crisis phases 1027.6 Conclusion 1057.7 References 105Chapter 8 Gender-Based Differences in the Impact of the Economic Crisis on Labor Market Flows in Southern Europe 107Maria SYMEONAKI, Maria KARAMESSINI and Glykeria STAMATOPOULOU8.1 Introduction 1078.2 Data, methods and limitations 1088.3 Results 1118.4 Conclusions and discussion 1118.5 References 119Chapter 9 Measuring Labor Market Transition Probabilities in Europe with Evidence from the EU-SILC 121Maria SYMEONAKI, Maria KARAMESSINI and Glykeria STAMATOPOULOU9.1 Introduction 1219.2 Data, methods and limitations 1229.3 Results 1249.4 Conclusions 1359.5 References 135Part 3 Student Assessment and Employment in Europe 137Chapter 10 Almost Graduated, Close to Employment? Taking into Account the Characteristics of Companies Recruiting at a University Job Placement Office 139Franca CRIPPA, Mariangela ZENGA and Paolo MARIANI10.1 Introduction 13910.2 Recruiters and graduates seeking an HEI common ground 14010.3 Web survey pitfalls: considerations for data collection 14110.4 Sampled recruiters: an outline 14410.5 Conclusion 14610.6 References 146Chapter 11 How Variation of Scores of the Programme for International Student Assessment can be Explained through Analysis of Information 149Valérie GIRARDIN, Justine LEQUESNE and Olivier THÉVENON11.1 Introduction 14911.2 Multiplicative models and Zighera’s parameterization 15111.3 Application to PISA surveys 15511.3.1 Data and variables 15511.3.2 Analysis of scores in mathematics 15711.3.3 Conclusion 16211.4 References 163Part 4 Visualization 165Chapter 12 A Topological Discriminant Analysis 167Rafik ABDESSELAM12.1 Introduction 16712.2 Topological equivalence 16812.3 Topological discriminant analysis 17112.4 Application example 17312.5 Conclusion and perspectives 17512.6 Appendix 17612.7 References 178Chapter 13 Using Graph Partitioning to Calculate PageRank in a Changing Network 179Christopher ENGSTRÖM and Sergei SILVESTROV13.1 Introduction 17913.1.1 Computing PageRank 18113.2 Changes in personalization vector 18213.3 Adding or removing edges between components 18413.3.1 Computations in practice 18613.3.2 Adding or removing an edge inside a component 18713.3.3 Maintaining the component structure 18913.4 Conclusions 19013.5 References 191Chapter 14 Visualizing the Political Spectrum of Germany by Contiguously Ordering the Party Policy Profiles 193Andranik TANGIAN14.1 Introduction 19314.2 The model 19514.3 Conclusions 20614.4 References 206List of Authors 209Index 213