Data Analysis in the AI Era

Models, Methods and Techniques
1. Auflage 2026
ISBN: 978-1-83669-139-6
Verlag: Wiley

Buch, Englisch, 304 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 603 g

Data Analysis in the AI Era covers the process of exploring and analyzing data from various sources for the purpose of extracting information, building models, and making decisions and inferences.

The AI and data analysis field is a scientific area that has grown enormously in recent decades, following a rapidly growing computer industry and the wide applicability of computational techniques in conjunction with new advances in analytic tools. Modeling enables data analysts to apply various statistical methods to the data they are investigating, identify relationships between variables, make predictions about future sets of data, and understand, interpret and visualize the extracted information more strategically. New research results have been developed and published, with many more in progress at the present time.

This book includes applications to health, demography, markets and climate, along with new mathematical and statistical techniques.

Autoren/Hrsg.

Bozeman, James R.

Skiadas, Christos H.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Introduction xiii
James R. BOZEMAN and Christos H. SKIADAS

Part 1. Health and Demography 1

Chapter 1. Standard and Fertility-adjusted Equitable Normal Pension Age 3
Tomáš FIALA, Jitka LANGHAMROVÁ and Jana VRABCOVÁ

1.1. Introduction 4
1.2. Methodology 6
1.3. Data source and calculations 8
1.4. Results 10
1.5. Conclusion 14
1.6. References 15

Chapter 2. Number of Centenarians in Brazil and Selected Countries: Evaluation of the Quality of Census Counting 17
Neir Antunes PAES, Rozane PEREIRA DE SOUSA and Vivian Conceição Alves Leite PEREIRA DO LAGO

2.1. Introduction 17
2.2. Methodology 18
2.3. Results of Review 2 21
2.4. Conclusion 29
2.5. References 29

Chapter 3. Optimal Semi-Markov Model Selection for Pediatric Obstructive Sleep Apnea Patient Data 31
Matthew FISCHER, Adam B. KASHLAK, Mathieu CHALIFOUR and Giseon HEO

3.1. Introduction 31
3.2. Sleep apnea data overview 33
3.3. Bayes factors 34
3.4. Semi-Markov models for sleep states 37
3.5. Sleep data model comparison 38
3.6. Conclusion 40
3.7. References 40

Chapter 4. An Efficient Determination Criterion-based Metric for Z-DNA Pattern Identification in the Epstein-Barr Virus Associated with Nasopharyngeal Carcinoma 43
James R. BOZEMAN, Jesús E. GARCÍA, V.A. GONZÁLEZ-LÓPEZ and D.S. SANTOS

4.1. Introduction 44
4.2. Results 47
4.3. Discussion 51
4.4. References 52Contents vii

Chapter 5. Investigating the Mediating Role of Dis/Trust in Government to Deal with the Pandemic in the Relationship Between Covid-19 Cases, the Impact of the Pandemic on Employment and Social Trust: Evidence From the 2020 European Social Survey for Four European Countries 55
Aggeliki YFANTI and Catherine MICHALOPOULOU

5.1. Introduction 56
5.2. Method 58
5.3. Results 62
5.4. Conclusion 67
5.5. References 68

Chapter 6. Joint Forecasting of Screening/Randomization Processes in Multicenter Clinical Trials and Predicting Optimal Enrollment Stopping Time 71
Volodymyr ANISIMOV and Leo GORTZAK

6.1. Introduction 72
6.2. Structure of screening stages 73
6.3. Predicting randomized patients from screening pool 74
6.4. Predicting the number of randomized patients 76
6.5. Randomization process from future arrivals 79
6.6. Parameter estimation 81viii Data Analysis in the AI Era
6.7. Implementation in R tool 82
6.8. Future considerations 86
6.9. Acknowledgment 86
6.10. References 86

Part 2. Applications 89

Chapter 7. Bidding Strategies Approaches for the Greek Electricity Market 91
Emmanuel KARAPIDAKIS, Marios NIKOLOGIANNIS and George MATALLIOTAKIS

7.1. Introduction 91
7.2. Methodology 93
7.3. Stand-alone and hybrid BESS bidding strategies 97
7.4. Conclusion 100
7.5. References 101

Chapter 8. Long-Term Memory, Event-Driven Dynamics and Predictive Power: An Analysis of Economic Policy Uncertainty and Market Volatility in the United States and UK 103
Christos FLOROS, George MATALLIOTAKIS and Fotis PAPATHEOFANOUS

8.1. Introduction 103
8.2. Background and theoretical foundations 105
8.3. Methodology 109
8.4. Empirical results 113
8.5. Discussion 122
8.6. Conclusion and future research 125
8.7. References 127
8.8. Appendix EPU US_Daily_Policy_Data 128

Chapter 9. Spatial Dependence in Extreme Precipitation: An Extreme Value Analysis in R 145
Dora PRATA GOMES and Maria Manuela NEVES

9.1. Introduction 145
9.2. Asymptotic models for spatial extremes 146
9.3. An application using the R environment – rainfall data in the North of Portugal 152
9.4. Final remarks 158
9.5. Acknowledgments 159
9.6. References 159

Chapter 10. Time Series and Cluster Analysis of Groundwater Level in Slovakia 161
Jana KALICKÁ, Dominika Sónak BALLOVÁ and Michalea ÈERVE?ANSKÁ

10.1. Introduction 161
10.2. Data specifications and methods. 162
10.3. Analysis of trend and periodic components in groundwater levels 163
10.4. The residuals component and ARMA modeling 166
10.5. Probe cluster analysis and visualization 168
10.6. Conclusion 170
10.7. Acknowledgments 171
10.8. References 171

Chapter 11. Coupon Collector Problem with Partial and Total Resets 173
Jelena JOCKOVIÆ and Bojana TODIÆ

11.1. Introduction and motivation 173
11.2. CCP with total resets 174
11.3. CCP with partial resets 176
11.4. Model comparison 180
11.5. Numerical results 182
11.6. Discussion 185
11.7. Acknowledgments 186
11.8. References 186

Chapter 12. The Relationship Between Quality of Life and Brain Drain 187
Aleksei N. KURBATSKII and Marina V. MIRONENKOVA

12.1. Introduction 187
12.2. Data and methodology 189
12.3. Results 193
12.4. Conclusion 197
12.5. Acknowledgments 198
12.6. References 198Contents xi

Part 3. Statistical Techniques 201

Chapter 13. A Unified Model for SPC and Maintenance in High Investigation Cost Processes with Multiple Quality Disruptions 203
Konstantina TSIOTA and Konstantinos A. TASIAS

13.1. Introduction 203
13.2. Problem statement 204
13.3. Mathematical model 206
13.4. Cost structure analysis 209
13.5. Optimization framework 211
13.6. Numerical analysis 212
13.7. Conclusion 214
13.8. References 216

Chapter 14. A Note on Spectral Risk Measures when Systemic Risk is Present 217
Georgios C. ZACHOS

14.1. Introduction and motivation 217
14.2. Preliminaries 221
14.3. Theoretical framework 223
14.4. Contribution 226
14.5. A suggested application 230
14.6. Conclusion 231
14.7. References 232
14.8. Appendix A 234
14.9. Appendix B 235

Chapter 15. Mutual Information and Pearson's Correlation in Analysis of Statistical Tests Suites: A Case Study 237
Elena ALMARAZ LUENGO

15.1. Introduction 237
15.2. ENT battery analysis 239
15.3. Conclusion 243
15.4. References 243

Chapter 16. Binary Regression and Non-monotonic Link Functions 245
Gloria GHENO

16.1. Introduction 246
16.2. Proposed method 247
16.3. Methodology 250
16.4. Comparison 253
16.5. Conclusion 258
16.6. References 259

List of Authors 261
Index 265

Über Autor(innen)

James R. Bozeman is a professor of Mathematics at the American University of Malta. He is also a Global Roster of Experts member at the International Science Council (ISC).

Christos H. Skiadas is the founder and former director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete, Greece. He is a prominent researcher in demography and was awarded Honorary Doctor of Accounting and Finance at the Hellenic Mediterranean University, Greece.