LEADER 07128nam 2200469 450 001 9910825723903321 005 20231205224300.0 010 $a1-119-82162-2 010 $a1-119-82172-X 010 $a1-119-82163-0 035 $a(CKB)4100000011809488 035 $a(MiAaPQ)EBC6528141 035 $a(Au-PeEL)EBL6528141 035 $a(OCoLC)1244626230 035 $a(CaSebORM)9781786306746 035 $a(EXLCZ)994100000011809488 100 $a20211014d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aApplied modeling techniques and data analysis 2 $efinancial, demographic, stochastic and statistical models and methods /$fedited by Yannis Dimotikalis [and three others] 210 1$aHoboken, New Jersey :$cWiley,$d[2021] 210 4$dİ2021 215 $a1 online resource (289 pages) 311 $a1-78630-674-3 327 $aCover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Preface -- Part 1. Financial and Demographic Modeling Techniques -- Chapter 1. Data Mining Application Issues in the Taxpayer Selection Process -- 1.1. Introduction -- 1.2. Materials and methods -- 1.2.1. Data -- 1.2.2. Interesting taxpayers -- 1.2.3. Enforced tax recovery proceedings -- 1.2.4. The models -- 1.3. Results -- 1.4. Discussion -- 1.5. Conclusion -- 1.6. References -- Chapter 2: Asymptotics of Implied Volatility in the Gatheral Double Stochastic Volatility Model -- 2.1. Introduction -- 2.2. The results -- 2.3. Proofs -- 2.4. References -- Chapter 3: New Dividend Strategies -- 3.1. Introduction -- 3.2. Model 1 -- 3.3. Model 2 -- 3.4. Conclusion and further results -- 3.5. Acknowledgments -- 3.6. References -- Chapter 4: Introduction of Reserves in Self-adjusting Steering of Parameters of a Pay-As-You-Go Pension Plan -- 4.1. Introduction -- 4.2. The pension system -- 4.3. Theoretical framework of the Musgrave rule -- 4.4. Transformation of the retirement fund -- 4.5. Conclusion -- 4.6. References -- Chapter 5: Forecasting Stochastic Volatility for Exchange Rates using EWMA -- 5.1. Introduction -- 5.2. Data -- 5.3. Empirical model -- 5.4. Exchange rate volatility forecasting -- 5.5. Conclusion -- 5.6. Acknowledgments -- 5.7. References -- Chapter 6: An Arbitrage-free Large Market Model for Forward Spread Curves -- 6.1. Introduction and background -- 6.1.1. Term-structure (interest rate) models -- 6.1.2. Forward-rate models versus spot-rate models -- 6.1.3. The Heath-Jarrow-Morton framework -- 6.1.4. Construction of our model -- 6.2. Construction of a market with infinitely many assets -- 6.2.1. The Cuchiero-Klein-Teichmann approach -- 6.2.2. Adapting Cuchiero-Klein-Teichmann's results to our objective -- 6.3. Existence, uniqueness and non-negativity. 327 $a6.3.1. Existence and uniqueness: mild -- 6.3.2. Non-negativity of solutions -- 6.4. Conclusion and future works -- 6.5. References -- Chapter 7: Estimating the Healthy Life Expectancy (HLE) in the Far Past: The Case of Sweden (1751-2016) with Forecasts to 2060 -- 7.1. Life expectancy and healthy life expectancy estimates -- 7.2. The logistic model -- 7.3. The HALE estimates and our direct calculations -- 7.4. Conclusion -- 7.5. References -- Chapter 8: Vaccination Coverage Against Seasonal Influenza of Workers in the Primary Health Care Units in the Prefecture of Chania -- 8.1. Introduction -- 8.2. Material and method -- 8.3. Results -- 8.4. Discussion -- 8.5. References -- Chapter 9: Some Remarks on the Coronavirus Pandemic in Europe -- 9.1. Introduction -- 9.2. Background -- 9.2.1. CoV pathogens -- 9.2.2. Clinical characteristics of COVID-19 -- 9.2.3. Diagnosis -- 9.2.4. Epidemiology and transmission of COVID-19 -- 9.2.5. Country response measures -- 9.2.6. The role of statistical research in the case of COVID-19 and its challenges -- 9.3. Materials and analyses -- 9.4. The first phase of the pandemic -- 9.5. Concluding remarks -- 9.6. References -- Part 2. Applied Stochastic and Statistical Models and Methods -- Chapter 10. The Double Flexible Dirichlet: A Structured Mixture Model for Compositional Data -- 10.1. Introduction -- 10.1.1. The flexible Dirichlet distribution -- 10.2. The double flexible Dirichlet distribution -- 10.2.1. Mixture components and cluster means -- 10.3. Computational and estimation issues -- 10.3.1. Parameter estimation: the EM algorithm -- 10.3.2. Simulation study -- 10.4. References -- Chapter 11. Quantization of Transformed Le?vy Measures -- 11.1. Introduction -- 11.2. Estimation strategy -- 11.3. Estimation of masses and the atoms -- 11.4. Simulation results -- 11.5. Conclusion -- 11.6. References. 327 $aChapter 12. A Flexible Mixture Regression Model for Bounded Multivariate Responses -- 12.1. Introduction -- 12.2. Flexible Dirichlet regression model -- 12.3. Inferential issues -- 12.4. Simulation studies -- 12.4.1. Simulation study 1: presence of outliers -- 12.4.2. Simulation study 2: generic mixture of two Dirichlet distributions -- 12.4.3. Simulation study 3: FD distribution -- 12.5. Discussion -- 12.6. References -- Chapter 13: On Asymptotic Structure of the CriticalGalton-Watson Branching Processes with Infinite Variance and Allowing Immigration -- 13.1. Introduction -- 13.2. Invariant measures of GW process -- 13.3. Invariant measures of GWPI -- 13.4. Conclusion -- 13.5. References -- Chapter 14. Properties of the Extreme Points of theJoint Eigenvalue Probability DensityFunction of the Wishart Matrix -- 14.1. Introduction -- 14.2. Background -- 14.3. Polynomial factorization of the Vandermonde andWishart matrices -- 14.4. Matrix norm of the Vandermonde and Wishart matrices -- 14.5. Condition number of the Vandermonde and Wishart matrices -- 14.6. Conclusion -- 14.7. Acknowledgments -- 14.8. References -- Chapter 15: Forecast Uncertainty of the Weighted TAR Predictor -- 15.1. Introduction -- 15.2. SETAR predictors and bootstrap prediction intervals -- 15.3. Monte Carlo simulation -- 15.4. References -- Chapter 16: Revisiting Transitions Between Superstatistics -- 16.1. Introduction -- 16.2. From superstatistic to transition between superstatistics -- 16.3. Transition confirmation -- 16.4. Beck's transition model -- 16.5. Conclusion -- 16.6. Acknowledgments -- 16.7. References -- Chapter 17: Research on Retrial Queue with Two-Way Communication in a Diffusion Environment -- 17.1. Introduction -- 17.2. Mathematical model -- 17.3. Asymptotic average characteristics -- 17.4. Deviation of the number of applications in the system. 327 $a17.5. Probability distribution density of device states -- 17.6. Conclusion -- 17.7. References -- List of Authors -- Index -- Other titles from iSTE in Innovation, Entrepreneurship and Management -- EULA. 606 $aData mining 615 0$aData mining. 676 $a006.312 702 $aDimotikalis$b Yiannis 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910825723903321 996 $aApplied modeling techniques and data analysis 2$94108970 997 $aUNINA