Data Analysis and Related Applications 4

Name: Data Analysis and Related Applications 4 | New Approaches
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New Approaches

Yiannis Dimotikalis Christos H. Skiadas(Herausgeber*in)

Wiley-ISTE (Verlag)

1. Auflage

Erschienen am 27. August 2024

416 Seiten

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Inhalt

Cover
Title Page
Copyright Page
Contents
Chapter 1. On the First-Passage Area of a One-Dimensional Diffusion Process with Stochastic Resetting
1.1. Formulation of the problem and general results
1.2. Brownian motion with resetting
1.2.1. Moments of the FPT
1.2.2. Moments of the FPA
1.2.3. Joint moment of A(x) and t (x)
1.2.4. Maximum displacement
1.3. Drifted Brownian motion with resetting
1.3.1. The Laplace transform of t (x)
1.3.2. Moments of the FPT
1.3.3. Mean of the FPA
1.3.4. Maximum displacement
1.4. References
Chapter 2. Statistical Analysis of Groundwater Level in Slovakia
2.1. Introduction
2.2. Data and methods
2.2.1. Change-point detection methods
2.2.2. Trend analysis
2.2.3. Spearman's rho test
2.3. Results
2.4. Conclusion
2.5. Acknowledgment
2.6. References
Chapter 3. Stochastic Processes Associated with Fully Nonlinear Parabolic Equations Arising in Financial Mathematics
3.1. Semilinear and fully nonlinear PDEs
3.2. BSDE, FBSDE and deep learning algorithms
3.3. Acknowledgments
3.4. References
Chapter 4. An Improved Shape Parameter Estimation Method for the Pareto Model
4.1. Introduction
4.2. Estimators under study
4.2.1. Common methods of estimation
4.2.2. Log-generalized probability weighted moment estimator
4.3. An algorithm for selection of the control parameter of the LGPWM shape parameter estimator
4.4. Numerical results
4.4.1. Simulation study
4.4.2. Real data analysis
4.5. Conclusion
4.6. Acknowledgments
4.7. References
Chapter 5. BSDE-. Scheme for the Heston Model: Valuation of American Options
5.1. Background
5.2. BSDE numerical schemes
5.2.1. The Heston model
5.2.2. BSDE representation of the Heston model
5.2.3. BSDE-. scheme under the Heston model
5.3. Numerical experimental studies: valuation of American options
5.4. Conclusion and future work
5.5. References
Chapter 6. Age-replacement Policy for Series Systems Under Parameter Uncertainty in Lifetime Distribution
6.1. Introduction
6.2.The model
6.2.1. Lifetime of units
6.2.2. Maintenance action and time
6.2.3. Maintenance policy
6.2.4. Cost model and cost rate
6.3. Optimization
6.3.1. A special case
6.4. Numerical example
6.5. Conclusion
6.6. References
Chapter 7. New Bicluster Algorithm for Trading
7.1. Introduction
7.2. Fuzzy logic and trading rules
7.3. Sentiment analysis, trading indicators and fuzzy rules
7.4. Conclusion
7.5. References
Chapter 8. A Flexible Generalization of the Latent Dirichlet Allocation
8.1. Introduction
8.2. Distributions on the simplex
8.3. Latent topic models
8.4. Collapsed Gibbs sampling
8.5. Simulation study
8.6. References
Chapter 9. Extreme Value Parameters Estimation: An Overview
9.1. Introduction and overview of extreme value theory
9.2. Some parameters of interest in EVT
9.3. EVI and EI estimation
9.3.1. EVI estimators
9.3.2. EI estimators
9.4. Extreme quantile estimation
9.5. Application to the daily mean flow discharge in river Tejo
9.6. Conclusion and work in progress
9.7. Acknowledgments
9.8. References
Chapter 10. Some Properties on Optimal Maintenance Policies for k-out-of-n:G Systems Considering Imperfect Repair with Controllable Repair Levels
10.1. Introduction
10.2. System description
10.2.1. Deterioration state
10.2.2. Maintenance actions
10.3. Total expected discounted cost
10.4. Optimization of maintenance policy
10.5. Numerical studies
10.5.1. Optimal maintenance policies for a two-out-of-three system
10.5.2. Sensitivity analysis
10.6. Conclusion
10.7. References
Chapter 11. Stochastic Orders and Reliability Properties for the Deficit at Ruin and Bounds for the Laplace Transform of a Compound Geometric Distribution
11.1. Introduction
11.2. Model description and results
11.3. Bounds for the LT of the maximal aggregate loss
11.4. Examples
11.5. References
Chapter 12. A New Family of Continuous Univariate Distributions with Applications in Actuarial Science
12.1. Introduction
12.2. Definitions and notations
12.3. Probability bounds
12.4. Aging properties and unimodality
12.5. Tail behavior of Dg +(h)
12.6. Conclusion
12.7. Acknowledgment
12.8. References
Chapter 13. Simple Form of Probability Density Functions via Sampling
13.1. Introduction
13.2. The sense and the method
13.2.1. The first step
13.2.2. The second step
13.3. Using sampling data
13.4. Results and discussion
13.5. References
Chapter 14. Optimizing Financial Trading Strategies Using Dynamic Bayesian Networks
14.1. Introduction
14.2. Theoretical framework
14.2.1. Inference for DBNs
14.2.2. Learning DBNs
14.2.3. Application of theory
14.2.4. Inference with known parameters
14.2.5. Learning unknown parameters
14.3. Methodology of analysis and results
14.4. Conclusion
14.5. References
Chapter 15. Quantitative Methods for Analysing the Risk and Timing of Bankruptcy of Small and Medium Enterprises
15.1.Introduction
15.2. Approaches to statistical modeling
15.3. Imbalanced data
15.3.1. Estimating the logistic regression model with imbalanced data
15.3.2. Separate sampling of good and bad units
15.3.3. Modifying the sample to deal with imbalanced data
15.4. Competing risks
15.5. Conclusion
15.6. References
Chapter 16. Network of Adaptive Frequency Oscillators in a Ballistic, Non-Gaussian, Noisy Environment
16.1. Introduction
16.2. Dynamics of the network
16.3. Analyzing the dynamics
16.3.1. The effect of the random vector B
16.3.2. Main results
16.4. Numerical simulations
16.5. Discussion and perspectives
16.6. Appendices
16.6.1. Appendix 1: Solution of the linear stochastic differential equation
16.6.2. Appendix 2: Calculations for changing back the variables, expected values and covariance matrices
16.6.3. Appendix 3: Distributions concerning the random vector B
16.6.4. Appendix 4: Eigenvalues of the Laplacian matrix of the "All-to-All" network
16.7. References
Chapter 17. Penalised Regression Adaptations of the Longstaff-Schwartz Algorithm for Pricing American Options
17.1. Introduction
17.2. The Longstaff-Schwartz algorithm and proposed extensions
17.3. Stochastic processes in finance and relevant theoretical considerations
17.4. Simulation design
17.5. Results
17.6. Conclusion
17.7. References
Chapter 18. International Auditing Standards and Their Contribution to the Limitation of Accounting Fraud
18.1. Introduction
18.2. Literature review
18.2.1. International Auditing Standards
18.2.2. Accounting fraud - falsification of financial statements
18.2.3. The Fraud Triangle
18.2.4. Fraud Diamond
18.2.5. Detection and prevention of accounting fraud
18.3. Empirical analysis
18.3.1. Introduction
18.3.2. Sample
18.3.3. Methodology
18.3.4. Simple linear regression
18.3.5. Analysis of auditors' questionnaire data
18.3.6. Analysis of questionnaire data of large companies
18.3.7. Comparative analysis of auditors' and companies' results
18.4. Conclusion
18.5. References
Chapter 19. Equivariant Robust Estimators for Moment Condition Models
19.1. Introduction
19.2. Robust estimators for moment condition models
19.2.1. Statistical divergences
19.2.2. Definition of the estimators
19.3. Equivariance of robust minimum empirical divergence estimators
19.3.1. Groups of transformations, invariant models and equivariant estimators
19.3.2. Equivariance of robust minimum empirical divergence estimators
19.4. Acknowledgments
19.5. References
Chapter 20. Continuous Increasing Probability Density Functions: An Approach Through Sampling
20.1. Introduction
20.2. Theoretical approach
20.3. Examples for illustration
20.4. Results and discussion
20.5. References
Chapter 21. The Importance of the Initial Selection of Suppliers in the Food Service Divisions of Hotels, the Current Situation in the Supply Chain of Greece
21.1. Introduction
21.2. Literature review
21.3. Benefits of supply chain management
21.4. Research methodology
21.4.1. The questionnaire
21.5. Data analysis
21.5.1. Reliability analysis
21.5.2. Results
21.6. Discussion
21.7. Conclusion
21.8. References
Chapter 22. Compliance with IUU Fisheries of Manila Clams in the Tagus Estuary
22.1. Introduction
22.2. Research methodology
22.3. Analysis and interpretation of results
22.4. Conclusion
22.5. Acknowledgments
22.6. References
Chapter 23. The Expectation of a Mixed Moving Average Process Subject to Ambiguous Lévy Basis
23.1. Introduction
23.2. supOU process
23.3. Optimization problems
23.3.1. Problem description
23.3.2. Problem D: Underestimation problem
23.3.3. Problem U: Overestimation problem
23.4. Application
23.4.1. Study sites
23.4.2. Parameter estimation
23.4.3. Results and discussion
23.5. Conclusion
23.6. Acknowledgments
23.7. References
List of Authors
Index
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