Applied modeling techniques and data analysis 2 : financial, demographic, stochastic and statistical models and methods / edited by Yannis Dimotikalis [and three others].

Format:

Book

Contributor:

Dimotikalis, Yiannis, editor.

Language:

English

Subjects (All):

Data mining.

Physical Description:

1 online resource (289 pages)

Place of Publication:

Hoboken, New Jersey : Wiley, [2021]

Summary:

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.

Contents:

Cover

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.

6.3.1. 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 Lévy 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.

Chapter 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 Critical Galton-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 the Joint Eigenvalue Probability Density Function of the Wishart Matrix

14.1. Introduction

14.2. Background

14.3. Polynomial factorization of the Vandermonde and Wishart 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.

17.5. Probability distribution density of device states

17.6. Conclusion

17.7. References

List of Authors

Index

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Notes:

Description based on print version record.

ISBN:

9781119821625

1119821622

9781119821724

111982172X

9781119821632

1119821630

OCLC:

1244626230