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Data Analysis and Related Applications 3


Data Analysis and Related Applications 3

Theory and Practice, New Approaches
1. Aufl.

von: Yiannis Dimotikalis, Christos H. Skiadas

142,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 10.04.2024
ISBN/EAN: 9781394284054
Sprache: englisch
Anzahl Seiten: 304

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Beschreibungen

<p>The book is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians who have been working at the forefront of data analysis and related applications, arising from data science, operations research, engineering, machine learning or statistics. The chapters of this collaborative work represent a cross-section of current research interests in the above scientific areas. The collected material has been divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.</p> <p>The published data analysis methodology includes the updated state-of-the-art rapidly developed theory and applications of data expansion, both of which go through outstanding changes nowadays. New approaches are expected to deliver and have been developed, including Artificial Intelligence.</p>
<p><b>Part 1 Data Analysis Classification 1</b></p> <p><b>Chapter 1 Walking into the Digital Era: Comparison of the European Union Countries in the Last Decade 3</b><br /><i>Fernanda Otilia FIGUEIREDO and Adelaide FIGUEIREDO</i></p> <p>1.1 Introduction 3</p> <p>1.2 Double principal component analysis: a brief description 7</p> <p>1.3 Representation of the trajectories 8</p> <p>1.4 Some final conclusions 11</p> <p>1.5 Acknowledgements 12</p> <p>1.6 References 12</p> <p><b>Chapter 2 Multivariate Kernel Discrimination Applied to Bank Loan Classification 13</b><br /><i>Mark Anthony CARUANA and Gabriele LENTINI</i></p> <p>2.1 Introduction 13</p> <p>2.2 Multivariate kernel density estimation 14</p> <p>2.3 Kernel discriminant analysis 17</p> <p>2.4 Applying kernel discriminant analysis to local data 18</p> <p>2.5 Conclusion 25</p> <p>2.6 References 25</p> <p><b>Chapter 3 Introducing an Ontology of Adolescents' Digital Leisure 29</b><br /><i>George FILANDRIANOS, Aggeliki KAZANI, Dimitrios PARSANOGLOU, Maria SYMEONAKI and Giorgos STAMOU</i></p> <p>3.1 Introduction 29</p> <p>3.2 Related work 32</p> <p>3.3 Ontology 35</p> <p>3.4 Description of the ontology construction 36</p> <p>3.5 Data annotation 39</p> <p>3.6 Conclusions 41</p> <p>3.7 Acknowledgments 41</p> <p>3.8 References 41</p> <p><b>Chapter 4 Blackjack and the Kelly Bet: A Simulation Assessment of Selected Playing Strategies 43</b><br /><i>Jim FREEMAN and Haoyu MIAO</i></p> <p>4.1 Introduction 43</p> <p>4.2 Blackjack 44</p> <p>4.3 Kelly bet 46</p> <p>4.4 Simulation study 47</p> <p>4.5 Empirical results 48</p> <p>4.6 Conclusions 49</p> <p>4.7 References 50</p> <p><b>Part 2 Estimators 51</b></p> <p><b>Chapter 5 An Evaluation of the Efficiency of a Shape Parameter Estimator for the Log-logistic Distribution 53</b><br /><i>Frederico CAEIRO and Ayana MATEUS</i></p> <p>5.1 Introduction 53</p> <p>5.2 Estimation of the shape parameter 56</p> <p>5.3 Simulation study 58</p> <p>5.4 References 60</p> <p><b>Chapter 6 Restricted Minimum Density Power Divergence Estimator for Step-stress ALT with Nondestructive One-shot Devices 63</b><br /><i>Narayanaswamy BALAKRISHNAN, María JAENADA and Leandro PARDO</i></p> <p>6.1 Introduction 63</p> <p>6.2 Minimum density power divergence estimator and restricted minimum density power divergence estimator 65</p> <p>6.3 Influence function of the restricted minimum density power divergence estimator 68</p> <p>6.4 Applications of the restricted MDPDE 69</p> <p>6.5 Simulation study 73</p> <p>6.6 Conclusions 75</p> <p>6.7 References 75</p> <p><b>Part 3 Finance 77</b></p> <p><b>Chapter 7 Properties of American Options Under a Semi-Markov Modulated Black-Scholes Model 79</b><br /><i>Kouki TAKADA, Marko DIMITROV, Lu JIN and Ying NI</i></p> <p>7.1 Introduction 79</p> <p>7.2 American option pricing 81</p> <p>7.3 Exercising strategies 83</p> <p>7.4 Conclusion 93</p> <p>7.5 References 93</p> <p><b>Chapter 8 Numerical Studies of Implied Volatility Expansions Under the Gatheral Model 97</b><br /><i>Mohammed ALBUHAYRI, Marko DIMITROV, Ying NI and Anatoliy MALYARENKO</i></p> <p>8.1 Introduction 97</p> <p>8.2 Previous results 99</p> <p>8.3 Accuracy of the asymptotic expansions 102</p> <p>8.4 Numerical analysis 105</p> <p>8.5 Conclusion and future work 106</p> <p>8.6 Acknowledgments 106</p> <p>8.7 References 106</p> <p><b>Chapter 9 Constructing Trinominal Models Based on Cubature Method on Wiener Space: Applications to Pricing Financial Derivatives 109</b><br /><i>Hossein NOHROUZIAN, Anatoliy MALYARENKO and Ying NI</i></p> <p>9.1 Introduction and outline of this chapter 109</p> <p>9.2 Cubature formula in Black-Scholes and Black's models 110</p> <p>9.3 Constructing a trinomial tree via cubature formula 113</p> <p>9.4 Convergence to geometric Brownian motion 115</p> <p>9.5 Martingale probability measure 122</p> <p>9.6 Extension of the results and examples 124</p> <p>9.7 Discussion 129</p> <p>9.8 References 129</p> <p><b>Chapter 10 A Bayesian Approach to Measuring Risk on Portfolios with Many Assets 131</b><br /><i>Samuel BONELLO, David SUDA and Monique BORG INGUANEZ</i></p> <p>10.1 Introduction 131</p> <p>10.2, Dynamic principal component analysis 133</p> <p>10.3 The Bayesian GARCH(1,1) model 135</p> <p>10.4 Modeling a portfolio with many assets 137</p> <p>10.5 Forecasting and risk estimation 140</p> <p>10.6 Measuring predictive ability 143</p> <p>10.7 Conclusion 144</p> <p>10.8 Acknowledgments 145</p> <p>10.9 References 145</p> <p><b>Chapter 11 Financial Management of Four Hellenic Public Health Units Analysis and Evaluation through Numerical Indicators 147</b><br /><i>Maria SACHINIDOU and George MATALLIOTAKIS</i></p> <p>11.1 Introduction 148</p> <p>11.2 Theoretical framework 148</p> <p>11.3 Methodology 149</p> <p>11.4 Research results 149</p> <p>11.5 Conclusions 162</p> <p>11.6 References 163</p> <p><b>Part 4 Health Services 165</b></p> <p><b>Chapter 12 Lean Management as an Improvement Factor in Health Services The Case of Venizeleio General Hospital of Crete, Greece 167</b><br /><i>Eleni GENITSARIDI and George MATALLIOTAKIS</i></p> <p>12.1 Introduction 168</p> <p>12.2 Theoretical framework 168</p> <p>12.3 Purpose of the research 172</p> <p>12.4 Methodology 172</p> <p>12.5 Research results 172</p> <p>12.6 Conclusions 179</p> <p>12.7 References 180</p> <p><b>Chapter 13 Satisfaction of Employees in Primary and Secondary Healthcare Structures During the Pandemic Period in the Prefecture of Magnesia 183</b><br /><i>Sofia TRIKALLIOTI and George MATALLIOTAKIS</i></p> <p>13.1 Introduction 184</p> <p>13.2 The Covid-19 pandemic and its effects 184</p> <p>13.3 Job satisfaction of healthcare professionals 185</p> <p>13.4 Healthcare professionals and the burnout syndrome 186</p> <p>13.5 Research purpose 188</p> <p>13.6 Research methodology 188</p> <p>13.7 Research conclusions 189</p> <p>13.8 References 193</p> <p><b>Chapter 14 A Parametric Analysis of OpenFlow and P4 Protocols Based on Software Defined Networks 197</b><br /><i>Lincoln S PETER, Hlabishi I KOBO and Viranjay M SRIVASTAVA</i></p> <p>14.1 Introduction 198</p> <p>14.2 Motivation 200</p> <p>14.3 Challenges to the existing models 202</p> <p>14.4 Conclusions and future recommendations 205</p> <p>14.5 References 205</p> <p><b>Chapter 15 A Dynamic Neural Network Model for Accurate Recognition of Masked Faces 209</b><br /><i>Oladapo T IBITOYE and Viranjay M SRIVASTAVA</i></p> <p>15.1 Introduction 210</p> <p>15.2 Methodology 213</p> <p>15.3 Results and discussion 217</p> <p>15.4 Conclusions and future recommendations 220</p> <p><b>Chapter 16 An Action-based Monitoring Tool for Processes Subject to Multiple Quality Shifts 225</b><br /><i>Konstantina TSIOTA and Konstantinos A TASIAS</i></p> <p>16.1 Introduction 225</p> <p>16.2 Problem definition and assumptions 227</p> <p>16.3 Conventional versus proposed SPC approach 230</p> <p>16.4 Markov chain models 232</p> <p>16.5 Optimization problem 238</p> <p>16.6 Numerical analysis 239</p> <p>16.7 Conclusions 242</p> <p>16.8 References 242</p> <p><b>Chapter 17 Phi Divergence and Consistent Estimation for Stochastic Block Model 243</b><br /><i>Cyprien FERRARIS</i></p> <p>17.1 Introduction 243</p> <p>17.2 Statement of the problem 244</p> <p>17.3 Results 247</p> <p>17.4 Simulations 248</p> <p>17.5 Study of real dataset: email-Enron 250</p> <p>17.6 Summary and discussion 251</p> <p>17.7 Acknowledgment 252</p> <p>17.8 Appendix 252</p> <p>17.9 References 257</p> <p>List of Authors 259</p> <p>Index 263</p>
<p><b>Yiannis Dimotikalis</b> is Assistant Professor of Quantitative Methods in the Department of Management Science and Technology at Hellenic Mediterranean University, Greece.</p> <p><b>Christos H. Skiadas</b> was the Founder and Director of Data Analysis and Forecasting and Former Vice-Rector at the Technical University of Crete, Greece. He is the Chair of the Applied Stochastic Models and Data Analysis conference series.</p>

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