Statistical Techniques for Modelling Extreme Value Data and Related Applications 1st Edition by Haroon Barakat, Osama Khaled, El Sayed Nigm ISBN 1527532070 9781527532076

Statistical Techniques for Modelling Extreme Value Data and Related Applications 1st Edition by Haroon M. Barakat, Osama M. Khaled, El-Sayed M. Nigm – Ebook PDF Instant Download/Delivery: 1527532070, 978-1527532076
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Product details:

ISBN 10:    1527532070    
ISBN 13: 978-1527532076
Author:     Haroon M. Barakat, Osama M. Khaled, El-Sayed M. Nigm

Statistical Techniques for Modelling Extreme Value Data and Related Applications 1st Table of contents:

Chapter 1: Introduction to Extreme Value Theory

1.1 Overview of Extreme Value Theory (EVT)
1.2 Importance and Applications of EVT
1.3 Key Concepts in Extreme Value Theory
1.4 Historical Development of EVT
1.5 Motivation for Modelling Extreme Values

Chapter 2: Basics of Statistical Theory for Extreme Values

2.1 Probability Theory Basics for EVT
2.2 Distribution Functions and Their Role in EVT
2.3 The Generalized Extreme Value (GEV) Distribution
2.4 The Generalized Pareto Distribution (GPD)
2.5 Extreme Value Index and Tail Behavior

Chapter 3: Estimation Methods in Extreme Value Theory

3.1 Maximum Likelihood Estimation (MLE)
3.2 Bayesian Estimation Techniques
3.3 Moments-Based Estimations
3.4 Peak Over Threshold (POT) Method
3.5 Parametric and Non-Parametric Methods
3.6 Bootstrap and Resampling Techniques

Chapter 4: Modelling and Fitting Extreme Value Data

4.1 Fitting the GEV and GPD to Data
4.2 Goodness-of-Fit Tests for Extreme Value Models
4.3 Diagnostics for Extreme Value Models
4.4 Practical Challenges in Model Fitting
4.5 Case Studies in Fitting Extreme Value Data

Chapter 5: Applications of Extreme Value Theory

5.1 Extreme Value Modelling in Environmental Data
5.2 EVT in Finance and Insurance
5.3 Application of EVT in Engineering and Reliability Analysis
5.4 EVT in Hydrology and Climate Science
5.5 EVT for Risk Management and Decision Making

Chapter 6: Multivariate Extreme Value Theory

6.1 The Multivariate Generalized Extreme Value Distribution
6.2 Dependence Structures in Multivariate Extreme Value Theory
6.3 Copula Models and Their Applications
6.4 Multivariate EVT in Environmental and Financial Data
6.5 Simulation Techniques for Multivariate Extreme Values

Chapter 7: Spatial Extreme Value Modelling

7.1 Introduction to Spatial Extremes
7.2 Spatial Dependence and Spatial Tail Modelling
7.3 Statistical Models for Spatial Extreme Values
7.4 Applications in Climate and Meteorological Data
7.5 Techniques for Spatial Extreme Value Estimation

Chapter 8: Time Series Modelling of Extreme Values

8.1 Time Series Models for Extreme Value Data
8.2 Extreme Value Processes and Models
8.3 Threshold Models for Time Series Extremes
8.4 Application to Financial Market Data and Risk Assessment
8.5 Time-Dependent GEV and GPD Models

Chapter 9: Extreme Value Simulation and Computational Techniques

9.1 Simulation of Extreme Value Distributions
9.2 Monte Carlo Simulation for EVT Applications
9.3 Numerical Solutions and Approximation Techniques
9.4 Computational Tools for Extreme Value Modelling
9.5 Implementing EVT in R and Python

Chapter 10: Advances and Recent Trends in Extreme Value Modelling

10.1 Emerging Techniques in Extreme Value Theory
10.2 Multiscale Modelling of Extreme Events
10.3 Machine Learning Approaches in Extreme Value Modelling
10.4 The Role of Big Data in Extreme Value Applications
10.5 Future Directions in EVT Research

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