BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 2 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is 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.

Table of Contents:
Preface xi Yannis DIMOTIKALIS, Alex KARAGRIGORIOU, Christina PARPOULA and Christos H. SKIADAS Part 1. Financial and Demographic Modeling Techniques 1 Chapter 1. Data Mining Application Issues in the Taxpayer Selection Process 3 Mauro BARONE, Stefano PISANI and Andrea SPINGOLA 1.1. Introduction 3 1.2. Materials and methods 5 1.2.1. Data 5 1.2.2. Interesting taxpayers 6 1.2.3. Enforced tax recovery proceedings 9 1.2.4. The models 11 1.3. Results 13 1.4. Discussion 23 1.5. Conclusion 23 1.6. References 24 Chapter 2. Asymptotics of Implied Volatility in the Gatheral Double Stochastic Volatility Model 27 Mohammed ALBUHAYRI, Anatoliy MALYARENKO, Sergei SILVESTROV, Ying NI, Christopher ENGSTRÖM, Finnan TEWOLDE and Jiahui ZHANG 2.1. Introduction 27 2.2. The results 30 2.3. Proofs 30 2.4. References 38 Chapter 3. New Dividend Strategies 39 Ekaterina BULINSKAYA 3.1. Introduction 39 3.2. Model 1 41 3.3. Model 2 48 3.4. Conclusion and further results 51 3.5. Acknowledgments 51 3.6. References 52 Chapter 4. Introduction of Reserves in Self-adjusting Steering of Parameters of a Pay-As-You-Go Pension Plan 53 Keivan DIAKITE, Abderrahim OULIDI and Pierre DEVOLDER 4.1. Introduction 53 4.2. The pension system 54 4.3. Theoretical framework of the Musgrave rule 57 4.4. Transformation of the retirement fund 60 4.5. Conclusion 63 4.6. References 64 Chapter 5. Forecasting Stochastic Volatility for Exchange Rates using EWMA 65 Jean-Paul MURARA, Anatoliy MALYARENKO, Milica RANCIC and Sergei SILVESTROV 5.1. Introduction 65 5.2. Data 66 5.3. Empirical model 67 5.4. Exchange rate volatility forecasting 69 5.5. Conclusion 73 5.6. Acknowledgments 73 5.7. References 74 Chapter 6. An Arbitrage-free Large Market Model for Forward Spread Curves 75 Hossein NOHROUZIAN, Ying NI and Anatoliy MALYARENKO 6.1. Introduction and background 75 6.1.1. Term-structure (interest rate) models 76 6.1.2. Forward-rate models versus spot-rate models 77 6.1.3. The Heath–Jarrow–Morton framework 77 6.1.4. Construction of our model 78 6.2. Construction of a market with infinitely many assets 79 6.2.1. The Cuchiero–Klein–Teichmann approach 79 6.2.2. Adapting Cuchiero–Klein–Teichmann’s results to our objective 82 6.3. Existence, uniqueness and non-negativity 82 6.3.1. Existence and uniqueness: mild solutions 83 6.3.2. Non-negativity of solutions 85 6.4. Conclusion and future works 87 6.5. References 88 Chapter 7. Estimating the Healthy Life Expectancy (HLE) in the Far Past: The Case of Sweden (1751–2016) with Forecasts to 2060 91 Christos H. SKIADAS and Charilaos SKIADAS 7.1. Life expectancy and healthy life expectancy estimates 92 7.2. The logistic model 94 7.3. The HALE estimates and our direct calculations 95 7.4. Conclusion 96 7.5. References 96 Chapter 8. Vaccination Coverage Against Seasonal Influenza of Workers in the Primary Health Care Units in the Prefecture of Chania 97 Aggeliki MARAGKAKI and George MATALLIOTAKIS 8.1. Introduction 98 8.2. Material and method 98 8.3. Results 101 8.4. Discussion 105 8.5. References 107 Chapter 9. Some Remarks on the Coronavirus Pandemic in Europe 109 Konstantinos ZAFEIRIS and Marianna KOUKLI 9.1. Introduction 109 9.2. Background 110 9.2.1. CoV pathogens 110 9.2.2. Clinical characteristics of COVID-19 111 9.2.3. Diagnosis 113 9.2.4. Epidemiology and transmission of COVID-19 113 9.2.5. Country response measures 115 9.2.6. The role of statistical research in the case of COVID-19 and its challenges 119 9.3. Materials and analyses 119 9.4. The first phase of the pandemic 121 9.5. Concluding remarks 126 9.6. References 127 Part 2. Applied Stochastic and Statistical Models and Methods 135 Chapter 10. The Double Flexible Dirichlet: A Structured Mixture Model for Compositional Data 137 Roberto ASCARI, Sonia MIGLIORATI and Andrea ONGARO 10.1. Introduction 138 10.1.1. The flexible Dirichlet distribution 139 10.2. The double flexible Dirichlet distribution 140 10.2.1. Mixture components and cluster means 141 10.3. Computational and estimation issues 144 10.3.1. Parameter estimation: the EM algorithm 145 10.3.2. Simulation study 148 10.4. References 151 Chapter 11. Quantization of Transformed Lévy Measures 153 Mark Anthony CARUANA 11.1. Introduction 153 11.2. Estimation strategy 156 11.3. Estimation of masses and the atoms 159 11.4. Simulation results 165 11.5. Conclusion 166 11.6. References 167 Chapter 12. A Flexible Mixture Regression Model for Bounded Multivariate Responses 169 Agnese M. DI BRISCO and Sonia MIGLIORATI 12.1. Introduction 169 12.2. Flexible Dirichlet regression model 170 12.3. Inferential issues 172 12.4. Simulation studies 173 12.4.1. Simulation study 1: presence of outliers 174 12.4.2. Simulation study 2: generic mixture of two Dirichlet distributions 179 12.4.3. Simulation study3: FD distribution 180 12.5. Discussion 182 12.6. References 183 Chapter 13. On Asymptotic Structure of the Critical Galton–Watson Branching Processes with Infinite Variance and Allowing Immigration 185 Azam A. IMOMOV and Erkin E. TUKHTAEV 13.1. Introduction 185 13.2. Invariant measures of GW process 187 13.3. Invariant measures of GWPI 190 13.4. Conclusion 193 13.5. References 194 Chapter 14. Properties of the Extreme Points of the Joint Eigenvalue Probability Density Function of the Wishart Matrix 195 Asaph Keikara MUHUMUZA, Karl LUNDENGÅRD, Sergei SILVESTROV, John Magero MANGO and Godwin KAKUBA 14.1. Introduction 195 14.2. Background 196 14.3. Polynomial factorization of the Vandermonde and Wishart matrices 197 14.4. Matrix norm of the Vandermonde and Wishart matrices 200 14.5. Condition number of the Vandermonde and Wishart matrices 203 14.6. Conclusion 206 14.7. Acknowledgments 206 14.8. References 207 Chapter 15. Forecast Uncertainty of the Weighted TAR Predictor 211 Francesco GIORDANO and Marcella NIGLIO 15.1. Introduction 211 15.2. SETAR predictors and bootstrap prediction intervals 214 15.3. Monte Carlo simulation 218 15.4. References 222 Chapter 16. Revisiting Transitions Between Superstatistics 223 Petr JIZBA and Martin PROKŠ 16.1. Introduction 223 16.2. From superstatistic to transition between superstatistics 224 16.3. Transition confirmation 225 16.4. Beck’s transition model 227 16.5. Conclusion 230 16.6. Acknowledgments 231 16.7. References 231 Chapter 17. Research on Retrial Queue with Two-Way Communication in a Diffusion Environment 233 Viacheslav VAVILOV 17.1. Introduction 233 17.2. Mathematical model 234 17.3. Asymptotic average characteristics 236 17.4. Deviation of the number of applications in the system 241 17.5. Probability distribution density of device states 247 17.6. Conclusion 248 17.7. References 248 List of Authors 251 Index 255