Data analysis and related applications. Volume 1 : computational, algorithmic and applied economic data analysis / Konstantinos N Zafeiris [and four others], editors.

Format:

Book

Contributor:

Zafeiris, Konstantinos N, editor.

Series:

Innovation, entrepreneurship and management series. Big data, artificial intelligence and data analysis set ; Volume 9.

Big Data, Artificial Intelligence and Data Analysis Set ; Volume 9

Language:

English

Subjects (All):

Quantitative research.

Physical Description:

1 online resource (478 pages)

Place of Publication:

Hoboken, NJ : John Wiley and Sons Inc., [2022]

Summary:

The scientific field of data analysis is constantly expanding due to the rapid growth of the computer industry and the wide applicability of computational and algorithmic techniques, in conjunction with new advances in statistical, stochastic and analytic tools. There is a constant need for new, high-quality publications to cover the recent advances in all fields of science and engineering. This book is a collective work by a number of leading scientists, computer experts, analysts, engineers, mathematicians, probabilists and statisticians who have been working at the forefront of data analysis and related applications. The chapters of this collaborative work represent a cross-section of current concerns, developments and 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 related applications.

Contents:

Cover

Half-Title Page

Title Page

Copyright Page

Contents

Preface

Part 1

1. Performance of Evaluation of Diagnosis of Various Thyroid Diseases Using Machine Learning Techniques

1.1. Introduction

1.2. Data understanding

1.3. Modeling

1.4. Findings

1.5. Conclusion

1.6. References

2. Exploring Chronic Diseases' Spatial Patterns: Thyroid Cancer in Sicilian Volcanic Areas

2.1. Introduction

2.2. Epidemiological data and territory

2.3. Methodology

2.3.1. Spatial inhomogeneity and spatial dependence

2.3.2. Standardized incidence ratio (SIR)

2.3.3. Local Moran's I statistic

2.4. Spatial distribution of TC in eastern Sicily

2.4.1. SIR geographical variation

2.4.2. Estimate of the spatial attraction

2.5. Conclusion

2.6. References

3. Analysis of Blockchain-based Databases in Web Applications

3.1. Introduction

3.2. Background

3.2.1. Blockchain

3.2.2. Blockchain types

3.2.3. Blockchain-based web applications

3.2.4. Blockchain consensus algorithms

3.2.5. Other consensus algorithms

3.3. Analysis stack

3.3.1. Art Shop web application

3.3.2. SQL-based application

3.3.3. NoSQL-based application

3.3.4. Blockchain-based application

3.4. Analysis

3.4.1. Adding records

3.4.2. Query

3.4.3. Functionality

3.4.4. Security

3.5. Conclusion

3.6. References

4. Optimization and Asymptotic Analysis of Insurance Models

4.1. Introduction

4.2. Discrete-time model with reinsurance and bank loans

4.2.1. Model description

4.2.2. Optimization problem

4.2.3. Model stability

4.3. Continuous-time insurance model with dividends

4.3.1. Model description

4.3.2. Optimal barrier strategy

4.3.3. Special form of claim distribution

4.3.4. Numerical analysis

4.4. Conclusion and further research directions

4.5. References.

5. Statistical Analysis of TrafficVolume in the 25 de Abril Bridge

5.1. Introduction

5.2. Data

5.3. Methodology

5.3.1. Main limit results

5.3.2. Block maxima method

5.3.3. Largest order statistics method

5.3.4. Estimation of other tail parameters

5.4. Results and conclusion

5.5. Acknowledgements

5.6. References

6. Predicting the Risk of Gestational Diabetes Mellitus through Nearest Neighbor Classification

6.1. Introduction

6.2. Nearest neighbor methods

6.2.1. Background of the NN methods

6.2.2. The k-nearest neighbors method

6.2.3. The fixed-radius NN method

6.2.4. The kernel-NN method

6.2.5. Algorithms of the three considered NN methods

6.2.6. Parameter and distance metric selection

6.3. Experimental results

6.3.1. Dataset description

6.3.2. Variable selection and data splitting

6.3.3. Results

6.3.4. A discussion and comparison of results

6.4. Conclusion

6.5. References

7. Political Trust in National Institutions: The Significance of Items' Level of Measurement in the Validation of Constructs

7.1. Introduction

7.2. Methods

7.2.1. Participants

7.2.2. Instrument

7.2.3. Statistical analyses

7.3. Results

7.3.1. EFA results

7.3.2. CFA results

7.3.3. Scale construction and assessment

7.4. Conclusion

7.5. Funding

7.6. References

8. The State of the Art in Flexible Regression Models for Univariate Bounded Responses

8.1. Introduction

8.2. Regression model for bounded responses

8.2.1. Augmentation

8.2.2. Main distributions on the bounded support

8.2.3. Inference and

8.3. Case studies

8.3.1. Stress data

8.3.2. Reading data

8.4. References

9. Simulation Studies for a Special Mixture Regression Model with Multivariate Responses on the Simplex

9.1. Introduction

9.2. Dirichlet and EFD distributions.

9.3. Dirichlet and EFD regression models

9.3.1. Inference and

9.4. Simulation studies

9.4.1. Comments

9.5. References

Part 2

10. Numerical Studies of Implied Volatility Expansions Under the Gatheral Model

10.1. Introduction

10.2. Asymptotic expansions of implied volatility

10.3. Performance of the asymptotic expansions

10.4. Calibration using the asymptotic expansions

10.4.1. A partial calibration procedure

10.4.2. Calibration to synthetic and market data

10.5. Conclusion and future work

10.6. References

11. Performance Persistence of Polish Mutual Funds: Mobility Measures

11.1. Introduction

11.2. Literature review

11.3. Dataset and empirical design

11.4. Empirical results

11.5. Monthly perspective

11.6. Quarterly perspective

11.7. Yearly perspective

11.8. Conclusion

11.9. References

12. Invariant Description for a Batch Version of the UCB Strategy with Unknown Control Horizon

12.1. Introduction

12.2. UCB strategy

12.3. Batch version of the strategy

12.4. Invariant description with a unit control horizon

12.5. Simulation results

12.6. Conclusion

12.7. Affiliations

12.8. References

13. A New Non-monotonic Link Function for Beta Regressions

13.1. Introduction

13.2. Model

13.3. Estimation

13.4. Comparison

13.5. Conclusion

13.6. References

14. A Method of Big Data Collection and Normalization for Electronic Engineering Applications

14.1. Introduction

14.2. Machine learning (ML) in electronic engineering

14.2.1. Data acquisition

14.2.2. Accessing the data repositories

14.2.3. Data storage and management

14.3. Electronic engineering applications - data science

14.4. Conclusion and future work

14.5. References.

15. Stochastic Runge-Kutta Solvers Based on Markov Jump Processes and Applications to Non-autonomous Systems of Differential Equations

15.1. Introduction

15.2. Description of the method

15.2.1. The direct simulation method

15.2.2. Picard iterations

15.2.3. Runge-Kutta steps

15.3. Numerical examples

15.3.1. The Lorenz system

15.3.2. A combustion model

15.4. Conclusion

15.5. References

16. Interpreting a Topological Measure of Complexity for Decision Boundaries

16.1. Introduction

16.2. Persistent homology

16.3. Methodology

16.3.1. Neural networks and binary classification

16.3.2. Persistent homology of a decision boundary

16.3.3. Procedure

16.4. Experiments and results

16.4.1. Three-dimensional binary classification

16.4.2. Data divided by a hyperplane

16.5. Conclusion and discussion

16.6. References

17. The Minimum Renyi's Pseudodistance Estimators for Generalized Linear Models

17.1. Introduction

17.2. The minimum RP estimators for the GLM model: asymptotic distribution

17.3. Example: Poisson regression model

17.3.1. Real data application

17.4. Conclusion

17.5. Acknowledgments

17.6. Appendix

17.6.1. Proof of Theorem 1

17.7. References

18. Data Analysis based on Entropies and Measures of Divergence

18.1. Introduction

18.2. Divergence measures

18.3. Tests of fit based on Φ−divergence measures

18.4. Simulations

18.5. References

Part 3

19. Geographically Weighted Regression for Official Land Prices and their Temporal Variation in Tokyo

19.1. Introduction

19.2. Models and methodology

19.3. Data analysis

19.3.1. Data

19.3.2. Results

19.4. Conclusion

19.5. Acknowledgments

19.6. References

20. Software Cost Estimation Using Machine Learning Algorithms

20.1. Introduction

20.2. Methodology

20.2.1. Dataset.

20.2.2. Model

20.2.3. Evaluating the performance of the model

20.3. Results and discussion

20.4. Conclusion

20.5. References

21. Monte Carlo Accuracy Evaluation of Laser Cutting Machine

21.1. Introduction

21.2. Mathematical model of a pintograph

21.3. Monte Carlo simulator

21.4. Simulation results

21.5. Conclusion

21.6. Acknowledgments

21.7. References

22. Using Parameters of Piecewise Approximation by Exponents for Epidemiological Time Series Data Analysis

22.1. Introduction

22.2. Deriving equations for moving exponent parameters

22.3. Validation of derived equations by using synthetic data

22.4. Using derived equations to analyze real-life Covid-19 data

22.5. Conclusion

22.6. References

23. The Correlation Between Oxygen Consumption and Excretion of Carbon Dioxide in the Human Respiratory Cycle

23.1. Introduction

23.2. Respiratory function physiology: ventilation-perfusion ratio

23.3. The basic principle of operation of artificial lung ventilation devices: patient monitoring parameters

23.4. The algorithm for monitoring the carbon emissions and oxygen consumption

23.5. Results

23.6. Conclusion

23.7. References

Part 4

24. Approximate Bayesian Inference Using the Mean-Field Distribution

24.1. Introduction

24.2. Inference problem in a symmetric population system

24.2.1. Example of a symmetric system describing plant competition

24.2.2. Inference problem of the Schneider system, in a more general setting

24.3. Properties of the mean-field distribution

24.4. Mean-field approximated inference

24.4.1. Case of systems admitting a mean-field limit

24.5. Conclusion

24.6. References

25. Pricing Financial Derivatives in the Hull-White Model Using Cubature Methods on Wiener Space

25.1. Introduction and outline.

25.2. Cubature formulae on Wiener space.

Notes:

Description based on print version record.

7.1. Introduction

Other Format:

Print version: Zafeiris, Konstantinos N. Data Analysis and Related Applications, Volume 1

ISBN:

9781394165513

139416551X

9781394165490

1394165498

OCLC:

1338838293