Data Analysis and Related Applications 3 : Theory and Practice, New Approaches

Data Analysis and Related Applications 3 Theory and Practice, New Approaches

The book is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians who have been working at the forefront of data analysis and related applications, arising from data science, operations research, engineering, machine learning or statistics. The ch...

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Bibliographic Details
Main Author: Dimotikalis, Yiannis (-)
Other Authors: Skiadas, Christos H.
Format: eBook
Language:Inglés
Published: Newark : John Wiley & Sons, Incorporated 2024.
Edition:1st ed
Series:Innovation, entrepreneurship and management series. Big data, artificial intelligence and data analysis set ; v. 11.
Subjects:
Quantitative research.
Electronic data processing.
Mathematical statistics.
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009828027906719
Table of Contents:
  • Cover
  • Title Page
  • Copyright Page
  • Contents
  • Part 1. Data Analysis Classification
  • Chapter 1. Walking into the Digital Era: Comparison of the European Union Countries in the Last Decade
  • 1.1. Introduction
  • 1.1.1. The dataset
  • 1.1.2. Preliminary analysis of the data
  • 1.2. Double principal component analysis: a brief description
  • 1.3. Representation of the trajectories
  • 1.4. Some final conclusions
  • 1.5. Acknowledgements
  • 1.6. References
  • Chapter 2. Multivariate Kernel Discrimination Applied to Bank Loan Classification
  • 2.1. Introduction
  • 2.2. Multivariate kernel density estimation
  • 2.2.1. Kernel density estimator
  • 2.2.2. The optimal bandwidth
  • 2.3. Kernel discriminant analysis
  • 2.4. Applying kernel discriminant analysis to local data
  • 2.4.1. Description of data
  • 2.4.2. Variable selection
  • 2.5. Conclusion
  • 2.6. References
  • Chapter 3. Introducing an Ontology of Adolescents' Digital Leisure
  • 3.1. Introduction
  • 3.2. Related work
  • 3.3. Ontology
  • 3.4. Description of the ontology construction
  • 3.5. Data annotation
  • 3.6. Conclusions
  • 3.7. Acknowledgments
  • 3.8. References
  • Chapter 4. Blackjack and the Kelly Bet: A Simulation Assessment of Selected Playing Strategies
  • 4.1. Introduction
  • 4.2. Blackjack
  • 4.2.1. Rules of the game
  • 4.3. Kelly bet
  • 4.4. Simulation study
  • 4.4.1. Modeling assumptions
  • 4.5. Empirical results
  • 4.6. Conclusions
  • 4.7. References
  • Part 2. Estimators
  • Chapter 5. An Evaluation of the Efficiency of a Shape Parameter Estimator for the Log-logistic Distribution
  • 5.1. Introduction
  • 5.2. Estimation of the shape parameter
  • 5.2.1. Estimators under study
  • 5.2.2. Asymptotic properties of the estimators
  • 5.3. Simulation study
  • 5.4. References.
  • Chapter 6. Restricted Minimum Density Power Divergence Estimator for Step-stress ALT with Nondestructive One-shot Devices
  • 6.1. Introduction
  • 6.2. Minimum density power divergence estimator and restricted minimum density power divergence estimator
  • 6.3. Influence function of the restricted minimum density power divergence estimator
  • 6.4. Applications of the restricted MDPDE
  • 6.4.1. Rao-type test statistics
  • 6.4.2. DPD-based statistics
  • 6.5. Simulation study
  • 6.6. Conclusions
  • 6.7. References
  • Part 3. Finance
  • Chapter 7. Properties of American Options Under a Semi-Markov Modulated Black-Scholes Model
  • 7.1. Introduction
  • 7.2. American option pricing
  • 7.3. Exercising strategies
  • 7.3.1. Setting parameters
  • 7.3.2. Relationship between the option price and "economic situation, asset price and maturity"
  • 7.3.3. Relationship between option price and transition probability matrix
  • 7.3.4. Consideration of the optimal exercise region
  • 7.3.5. Condition of transition probability matrix for option price transition to be monotonous
  • 7.4. Conclusion
  • 7.5. References
  • Chapter 8. Numerical Studies of Implied Volatility Expansions Under the Gatheral Model
  • 8.1. Introduction
  • 8.2. Previous results
  • 8.3. Accuracy of the asymptotic expansions
  • 8.4. Numerical analysis
  • 8.5. Conclusion and future work
  • 8.6. Acknowledgments
  • 8.7. References
  • Chapter 9. Constructing Trinominal Models Based on Cubature Method on Wiener Space: Applications to Pricing Financial Derivatives
  • 9.1. Introduction and outline of this chapter
  • 9.2. Cubature formula in Black-Scholes and Black's models
  • 9.2.1. Black-Scholes model via cubature formula
  • 9.2.2. Black's model via cubature formula
  • 9.3. Constructing a trinomial tree via cubature formula
  • 9.3.1. A trinomial tree approximation for the Black-Scholes model.
  • 9.4. Convergence to geometric Brownian motion
  • 9.4.1. Convergence of finite-dimensional distribution
  • 9.4.2. Relative compactness
  • 9.5. Martingale probability measure
  • 9.6. Extension of the results and examples
  • 9.6.1. A trinomial tree approximation for Black's model
  • 9.6.2. Pricing American options using the trinomial tree
  • 9.7. Discussion
  • 9.8. References
  • Chapter 10. A Bayesian Approach to Measuring Risk on Portfolios with Many Assets
  • 10.1. Introduction
  • 10.2, Dynamic principal component analysis
  • 10.3. The Bayesian GARCH(1,1) model
  • 10.4. Modeling a portfolio with many assets
  • 10.5. Forecasting and risk estimation
  • 10.6. Measuring predictive ability
  • 10.7. Conclusion
  • 10.8. Acknowledgments
  • 10.9. References
  • Chapter 11. Financial Management ïf Four Hellenic Public Health Units. Analysis and Evaluation through Numerical Indicators
  • 11.1. Introduction
  • 11.2. Theoretical framework
  • 11.3. Methodology
  • 11.4. Research results
  • 11.4.1. Liquidity indicators
  • 11.4.2. Activity ratios
  • 11.4.3. Profitability ratios
  • 11.4.4. Capital adequacy and viability ratios
  • 11.5. Conclusions
  • 11.6. References
  • Part 4. Health Services
  • Chapter 12. Lean Management as an Improvement Factor in Health Services. The Case of Venizeleio General Hospital of Crete, Greece
  • 12.1. Introduction
  • 12.2. Theoretical framework
  • 12.3. Purpose of the research
  • 12.4. Methodology
  • 12.5. Research results
  • 12.6. Conclusions
  • 12.7. References
  • Chapter 13. Satisfaction of Employees in Primary and Secondary Healthcare Structures During the Pandemic Period in the Prefecture of Magnesia
  • 13.1. Introduction
  • 13.2. The Covid-19 pandemic and its effects
  • 13.3. Job satisfaction of healthcare professionals
  • 13.4. Healthcare professionals and the burnout syndrome
  • 13.5. Research purpose
  • 13.6. Research methodology.
  • 13.7. Research conclusions
  • 13.8. References
  • Chapter 14. A Parametric Analysis of OpenFlow and P4 Protocols Based on Software Defined Networks
  • 14.1. Introduction
  • 14.2. Motivation
  • 14.3. Challenges to the existing models
  • 14.3.1. A comparison with OpenFlow
  • 14.3.2. System: P4Consist
  • 14.4. Conclusions and future recommendations
  • 14.5. References
  • Chapter 15. A Dynamic Neural Network Model for Accurate Recognition of Masked Faces
  • 15.1. Introduction
  • 15.2. Methodology
  • 15.2.1. Data collection and preprocessing
  • 15.2.2. Model training and validation
  • 15.2.3. System implementation
  • 15.2.4. System evaluation
  • 15.3. Results and discussion
  • 15.3.1. Training accuracy
  • 15.3.2. Validation accuracy
  • 15.3.3. Training loss
  • 15.3.4. Validation loss
  • 15.3.5. Overall accuracy
  • 15.4. Conclusions and future recommendations
  • 15.5. References
  • Chapter 16. An Action-based Monitoring Tool for Processes Subject to Multiple Quality Shifts
  • 16.1. Introduction
  • 16.2. Problem definition and assumptions
  • 16.3. Conventional versus proposed SPC approach
  • 16.3.1. Conventional SPC approach
  • 16.3.2. Proposed SPC approach
  • 16.4. Markov chain models
  • 16.4.1. Transition probability matrix
  • 16.4.2. Transition probabilities
  • 16.4.3. Expected cost per time unit
  • 16.5. Optimization problem
  • 16.6. Numerical analysis
  • 16.6.1. Numerical examples
  • 16.6.2. Performance comparisons
  • 16.7. Conclusions
  • 16.8. References
  • Chapter 17. Phi Divergence and Consistent Estimation for Stochastic Block Model
  • 17.1. Introduction
  • 17.2. Statement of the problem
  • 17.3. Results
  • 17.4. Simulations
  • 17.5. Study of real dataset: email-Enron
  • 17.6. Summary and discussion
  • 17.7. Acknowledgment
  • 17.8. Appendix
  • 17.9. References
  • List of Authors
  • Index
  • EULA.

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