Applied Modeling Techniques and Data Analysis 2

Yannis Dimotikalis is Assistant Professor within the Department of Management Science and Technology at the Hellenic Mediterranean University, Greece. Alex Karagrigoriou is Professor of Probability and Statistics, Deputy Director of Graduate Studies in Statistics and Actuarial-Financial Mathematics, and Director of the Laboratory of Statistics and Data Analysis within the Department of Statistics and Actuarial-Financial Mathematics at the University of the Aegean, Greece. Christina Parpoula is Assistant Professor of Applied Statistics and Research Methodology within the Department of Psychology at the Panteion University of Social and Political Sciences, Greece. Christos H. Skiadas is Former Vice-Rector at the Technical University of Crete, Greece, and founder of its Data Analysis and Forecasting Laboratory. He continues his research in ManLab, within the faculty�s Department of Production Engineering and Management.

• Preface xiYannis DIMOTIKALIS, Alex KARAGRIGORIOU, Christina PARPOULA and Christos H. SKIADASPart 1. Financial and Demographic Modeling Techniques 1Chapter 1. Data Mining Application Issues in the Taxpayer Selection Process 3Mauro BARONE, Stefano PISANI and Andrea SPINGOLA1.1. Introduction 31.2. Materials and methods 51.2.1. Data 51.2.2. Interesting taxpayers 61.2.3. Enforced tax recovery proceedings 91.2.4. The models 111.3. Results 131.4. Discussion 231.5. Conclusion 231.6. References 24Chapter 2. Asymptotics of Implied Volatility in the Gatheral Double Stochastic Volatility Model 27Mohammed ALBUHAYRI, Anatoliy MALYARENKO, Sergei SILVESTROV, Ying NI, Christopher ENGSTRÖM, Finnan TEWOLDE and Jiahui ZHANG2.1. Introduction 272.2. The results 302.3. Proofs 302.4. References 38Chapter 3. New Dividend Strategies 39Ekaterina BULINSKAYA3.1. Introduction 393.2. Model 1 413.3. Model 2 483.4. Conclusion and further results 513.5. Acknowledgments 513.6. References 52Chapter 4. Introduction of Reserves in Self-adjusting Steering of Parameters of a Pay-As-You-Go Pension Plan 53Keivan DIAKITE, Abderrahim OULIDI and Pierre DEVOLDER4.1. Introduction 534.2. The pension system 544.3. Theoretical framework of the Musgrave rule 574.4. Transformation of the retirement fund 604.5. Conclusion 634.6. References 64Chapter 5. Forecasting Stochastic Volatility for Exchange Rates using EWMA 65Jean-Paul MURARA, Anatoliy MALYARENKO, Milica RANCIC and Sergei SILVESTROV5.1. Introduction 655.2. Data 665.3. Empirical model 675.4. Exchange rate volatility forecasting 695.5. Conclusion 735.6. Acknowledgments 735.7. References 74Chapter 6. An Arbitrage-free Large Market Model for Forward Spread Curves 75Hossein NOHROUZIAN, Ying NI and Anatoliy MALYARENKO6.1. Introduction and background 756.1.1. Term-structure (interest rate) models 766.1.2. Forward-rate models versus spot-rate models 776.1.3. The Heath–Jarrow–Morton framework 776.1.4. Construction of our model 786.2. Construction of a market with infinitely many assets 796.2.1. The Cuchiero–Klein–Teichmann approach 796.2.2. Adapting Cuchiero–Klein–Teichmann’s results to our objective 826.3. Existence, uniqueness and non-negativity 826.3.1. Existence and uniqueness: mild solutions 836.3.2. Non-negativity of solutions 856.4. Conclusion and future works 876.5. References 88Chapter 7. Estimating the Healthy Life Expectancy (HLE) in the Far Past: The Case of Sweden (1751–2016) with Forecasts to 2060 91Christos H. SKIADAS and Charilaos SKIADAS7.1. Life expectancy and healthy life expectancy estimates 927.2. The logistic model 947.3. The HALE estimates and our direct calculations 957.4. Conclusion 967.5. References 96Chapter 8. Vaccination Coverage Against Seasonal Influenza of Workers in the Primary Health Care Units in the Prefecture of Chania 97Aggeliki MARAGKAKI and George MATALLIOTAKIS8.1. Introduction 988.2. Material and method 988.3. Results 1018.4. Discussion 1058.5. References 107Chapter 9. Some Remarks on the Coronavirus Pandemic in Europe 109Konstantinos ZAFEIRIS and Marianna KOUKLI9.1. Introduction 1099.2. Background 1109.2.1. CoV pathogens 1109.2.2. Clinical characteristics of COVID-19 1119.2.3. Diagnosis 1139.2.4. Epidemiology and transmission of COVID-19 1139.2.5. Country response measures 1159.2.6. The role of statistical research in the case of COVID-19 and its challenges 1199.3. Materials and analyses 1199.4. The first phase of the pandemic 1219.5. Concluding remarks 1269.6. References 127Part 2. Applied Stochastic and Statistical Models and Methods 135Chapter 10. The Double Flexible Dirichlet: A Structured Mixture Model for Compositional Data 137Roberto ASCARI, Sonia MIGLIORATI and Andrea ONGARO10.1. Introduction 13810.1.1. The flexible Dirichlet distribution 13910.2. The double flexible Dirichlet distribution 14010.2.1. Mixture components and cluster means 14110.3. Computational and estimation issues 14410.3.1. Parameter estimation: the EM algorithm 14510.3.2. Simulation study 14810.4. References 151Chapter 11. Quantization of Transformed Lévy Measures 153Mark Anthony CARUANA11.1. Introduction 15311.2. Estimation strategy 15611.3. Estimation of masses and the atoms 15911.4. Simulation results 16511.5. Conclusion 16611.6. References 167Chapter 12. A Flexible Mixture Regression Model for Bounded Multivariate Responses 169Agnese M. DI BRISCO and Sonia MIGLIORATI12.1. Introduction 16912.2. Flexible Dirichlet regression model 17012.3. Inferential issues 17212.4. Simulation studies 17312.4.1. Simulation study 1: presence of outliers 17412.4.2. Simulation study 2: generic mixture of two Dirichlet distributions 17912.4.3. Simulation study3: FD distribution 18012.5. Discussion 18212.6. References 183Chapter 13. On Asymptotic Structure of the Critical Galton–Watson Branching Processes with Infinite Variance and Allowing Immigration 185Azam A. IMOMOV and Erkin E. TUKHTAEV13.1. Introduction 18513.2. Invariant measures of GW process 18713.3. Invariant measures of GWPI 19013.4. Conclusion 19313.5. References 194Chapter 14. Properties of the Extreme Points of the Joint Eigenvalue Probability Density Function of the Wishart Matrix 195Asaph Keikara MUHUMUZA, Karl LUNDENGÅRD, Sergei SILVESTROV, John Magero MANGO and Godwin KAKUBA14.1. Introduction 19514.2. Background 19614.3. Polynomial factorization of the Vandermonde and Wishart matrices 19714.4. Matrix norm of the Vandermonde and Wishart matrices 20014.5. Condition number of the Vandermonde and Wishart matrices 20314.6. Conclusion 20614.7. Acknowledgments 20614.8. References 207Chapter 15. Forecast Uncertainty of the Weighted TAR Predictor 211Francesco GIORDANO and Marcella NIGLIO15.1. Introduction 21115.2. SETAR predictors and bootstrap prediction intervals 21415.3. Monte Carlo simulation 21815.4. References 222Chapter 16. Revisiting Transitions Between Superstatistics 223Petr JIZBA and Martin PROKŠ16.1. Introduction 22316.2. From superstatistic to transition between superstatistics 22416.3. Transition confirmation 22516.4. Beck’s transition model 22716.5. Conclusion 23016.6. Acknowledgments 23116.7. References 231Chapter 17. Research on Retrial Queue with Two-Way Communication in a Diffusion Environment 233Viacheslav VAVILOV17.1. Introduction 23317.2. Mathematical model 23417.3. Asymptotic average characteristics 23617.4. Deviation of the number of applications in the system 24117.5. Probability distribution density of device states 24717.6. Conclusion 24817.7. References 248List of Authors 251Index 255