Details

Data Analysis and Applications 2


Data Analysis and Applications 2

Utilization of Results in Europe and Other Topics
1. Aufl.

von: Christos H. Skiadas, James R. Bozeman

139,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 07.03.2019
ISBN/EAN: 9781119579533
Sprache: englisch
Anzahl Seiten: 256

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Beschreibungen

This series of books collects a diverse array of work that provides the reader with theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.<br /><br />Volume 2 begins with an introductory chapter by Gilbert Saporta, a leading expert in the field, who summarizes the developments in data analysis over the last 50 years. The book is then divided into four parts: Part 1 examines (in)dependence relationships, innovation in the Nordic countries, dentistry journals, dependence among growth rates of GDP of V4 countries, emissions mitigation, and five-star ratings; Part 2 investigates access to credit for SMEs, gender-based impacts given Southern Europe’s economic crisis, and labor market transition probabilities; Part 3 looks at recruitment at university job-placement offices and the Program for International Student Assessment; and Part 4 examines discriminants, PageRank, and the political spectrum of Germany.
<p>Preface xi</p> <p>Introduction xiii<br /><i>Gilbert SAPORTA</i></p> <p><b>Part 1 Applications </b>1</p> <p><b>Chapter 1 Context-specific Independence in Innovation Study </b><b>3<br /></b><i>Federica NICOLUSSI</i> and <i>Manuela CAZZARO</i></p> <p>1.1 Introduction 3</p> <p>1.2 Parametrization for CS independencies 4</p> <p>1.3 Stratified chain graph models 6</p> <p>1.4 Application on real data 7</p> <p>1.5 Conclusion 12</p> <p>1.6 References 12</p> <p><b>Chapter 2 Analysis of the Determinants and Outputs of Innovation in the Nordic Countries </b><b>15<br /></b><i>Cátia ROSÁRIO</i>, <i>António Augusto COSTA</i> and <i>Ana LORGA DA SILVA</i></p> <p>2.1 Introduction 15</p> <p>2.2 Innovation 16</p> <p>2.3 Methodology 19</p> <p>2.4 Results 21</p> <p>2.5 Conclusion 25</p> <p>2.6 References 26</p> <p><b>Chapter 3 Bibliometric Variables Determining the Quality of a Dentistry Journal </b><b>29<br /></b><i>Pilar VALDERRAMA, Manuel ESCABIAS, Evaristo JIMÉNEZ-CONTRERAS, Mariano JVALDERRAMA</i> and <i>Pilar BACA</i></p> <p>3.1 Introduction 29</p> <p>3.2 Statistical methodology 30</p> <p>3.3 Results 32</p> <p>3.4 Conclusions 35</p> <p>3.5 Acknowledgment 35</p> <p>3.6 References 36</p> <p><b>Chapter 4 Analysis of Dependence among Growth Rates of GDP of V4 Countries Using Four-dimensional Vine Copulas </b><b>37<br /></b><i>Jozef KOMORNÍK</i>, <i>Magda KOMORNÍKOVÁ</i> and <i>Tomáš BACIGÁL</i></p> <p>4.1 Introduction 37</p> <p>4.2 Theory 38</p> <p>4.3 Results 42</p> <p>4.4 Conclusion and future work 45</p> <p>4.5 Acknowledgment 47</p> <p>4.6 References 47</p> <p><b>Chapter 5 Monitoring the Compliance of Countries on Emissions Mitigation Using Dissimilarity Indices </b><b>49<br /></b><i>Eleni KETZAKI, Stavros RALLAKIS, Nikolaos FARMAKIS</i> and <i>Eftichios SARTZETAKIS</i></p> <p>5.1 Introduction 49</p> <p>5.2 The proposed method 50</p> <p>5.2.1 Description of method for individual data 51</p> <p>5.2.2 Description of method for grouped data 52</p> <p>5.3 Application of method 53</p> <p>5.3.1 Application of method for individual data 54</p> <p>5.3.2 Application of method for grouped data 55</p> <p>5.4 Conclusions 55</p> <p>5.5 Appendix 57</p> <p>5.6 References 58</p> <p><b>Chapter 6 Maximum Entropy and Distributions of Five-Star Ratings </b><b>59<br /></b><i>Yiannis DIMOTIKALIS</i></p> <p>6.1 Introduction 59</p> <p>6.2 Entropy framework to five-star ratings 60</p> <p>6.3 Maximum entropy of ratings for values k = 1,2,3,,30 66</p> <p>6.3.1 Ratings with two outcomes (k = 1) 66</p> <p>6.3.2 Ratings with three Outcomes (k=2) 69</p> <p>6.3.3 Ratings with four outcomes (k=3) 73</p> <p>6.3.4 Ratings with five outcomes (k = 4) 76</p> <p>6.3.5 Ratings entropy for outcomes k>4 80</p> <p>6.3.6 Maximum entropy constraints for the binomial distribution 82</p> <p>6.4 Application to real five-star rating data 83</p> <p>6.5 Conclusions 86</p> <p>6.6 References 86</p> <p><b>Part 2 The Impact of the Economic and Financial Crisis in Europe </b><b>89</b></p> <p><b>Chapter 7 Access to Credit for SMEs after the 2008 Financial Crisis: The Northern Italian Perspective </b><b>91<br /></b><i>Cinzia COLAPINTO</i> and <i>Mariangela ZENGA</i></p> <p>7.1 Introduction 91</p> <p>7.2 Italian SMEs and access to credit 92</p> <p>7.3 The data 93</p> <p>7.4 Methodology 94</p> <p>7.5 Analysis and discussion 97</p> <p>7.5.1 The measure for the Great Recession period (2008–2012) 97</p> <p>7.5.2 The measure for the recovery period (2013–2015) 99</p> <p>7.5.3 Comparing the two crisis phases 102</p> <p>7.6 Conclusion 105</p> <p>7.7 References 105</p> <p><b>Chapter 8 Gender-Based Differences in the Impact of the Economic Crisis on Labor Market Flows in Southern Europe </b><b>107<br /></b><i>Maria SYMEONAKI</i>, <i>Maria KARAMESSINI</i> and <i>Glykeria STAMATOPOULOU</i></p> <p>8.1 Introduction 107</p> <p>8.2 Data, methods and limitations 108</p> <p>8.3 Results 111</p> <p>8.4 Conclusions and discussion 111</p> <p>8.5 References 119</p> <p><b>Chapter 9 Measuring Labor Market Transition Probabilities in Europe with Evidence from the EU-SILC </b><b>121<br /></b><i>Maria SYMEONAKI, Maria KARAMESSINI</i> and <i>Glykeria STAMATOPOULOU</i></p> <p>9.1 Introduction 121</p> <p>9.2 Data, methods and limitations 122</p> <p>9.3 Results 124</p> <p>9.4 Conclusions 135</p> <p>9.5 References 135</p> <p><b>Part 3 Student Assessment and Employment in Europe </b><b>137</b></p> <p><b>Chapter 10 Almost Graduated, Close to Employment? Taking into Account the Characteristics of Companies Recruiting at a University Job Placement Office </b><b>139<br /></b><i>Franca CRIPPA, Mariangela ZENGA</i> and <i>Paolo MARIANI</i></p> <p>10.1 Introduction 139</p> <p>10.2 Recruiters and graduates seeking an HEI common ground 140</p> <p>10.3 Web survey pitfalls: considerations for data collection 141</p> <p>10.4 Sampled recruiters: an outline 144</p> <p>10.5 Conclusion 146</p> <p>10.6 References 146</p> <p><b>Chapter 11 How Variation of Scores of the Programme for International Student Assessment can be Explained through Analysis of Information </b><b>149<br /></b><i>Valérie GIRARDIN, Justine LEQUESNE</i> and <i>Olivier THÉVENON</i></p> <p>11.1 Introduction 149</p> <p>11.2 Multiplicative models and Zighera’s parameterization 151</p> <p>11.3 Application to PISA surveys 155</p> <p>11.3.1 Data and variables 155</p> <p>11.3.2 Analysis of scores in mathematics 157</p> <p>11.3.3 Conclusion 162</p> <p>11.4 References 163</p> <p><b>Part 4 Visualization </b><b>165</b></p> <p><b>Chapter 12 A Topological Discriminant Analysis </b><b>167<br /></b><i>Rafik ABDESSELAM</i></p> <p>12.1 Introduction 167</p> <p>12.2 Topological equivalence 168</p> <p>12.3 Topological discriminant analysis 171</p> <p>12.4 Application example 173</p> <p>12.5 Conclusion and perspectives 175</p> <p>12.6 Appendix 176</p> <p>12.7 References 178</p> <p><b>Chapter 13 Using Graph Partitioning to Calculate PageRank in a Changing Network </b><b>179<br /></b><i>Christopher ENGSTRÖM</i> and <i>Sergei SILVESTROV</i></p> <p>13.1 Introduction 179</p> <p>13.1.1 Computing PageRank 181</p> <p>13.2 Changes in personalization vector 182</p> <p>13.3 Adding or removing edges between components 184</p> <p>13.3.1 Computations in practice 186</p> <p>13.3.2 Adding or removing an edge inside a component 187</p> <p>13.3.3 Maintaining the component structure 189</p> <p>13.4 Conclusions 190</p> <p>13.5 References 191</p> <p><b>Chapter 14 Visualizing the Political Spectrum of Germany by Contiguously Ordering the Party Policy Profiles </b><b>193<br /></b><i>Andranik TANGIAN</i></p> <p>14.1 Introduction 193</p> <p>14.2 The model 195</p> <p>14.3 Conclusions 206</p> <p>14.4 References 206</p> <p>List of Authors 209</p> <p>Index 213</p>
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.<br /><br />James R. Bozeman holds a PhD in Mathematics from Dartmouth College, USA, and is Professor of Mathematics at the American University of Malta.
This series of books collects a diverse array of work that provides the reader with theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.<br /><br />Volume 2 begins with an introductory chapter by Gilbert Saporta, a leading expert in the field, who summarizes the developments in data analysis over the last 50 years. The book is then divided into four parts: Part 1 examines (in)dependence relationships, innovation in the Nordic countries, dentistry journals, dependence among growth rates of GDP of V4 countries, emissions mitigation, and five-star ratings; Part 2 investigates access to credit for SMEs, gender-based impacts given Southern Europe’s economic crisis, and labor market transition probabilities; Part 3 looks at recruitment at university job-placement offices and the Program for International Student Assessment; and Part 4 examines discriminants, PageRank, and the political spectrum of Germany.

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