The Birnbaum-Saunders Distribution

The Birnbaum-Saunders Distribution presents the statistical theory, methodology, and applications of the Birnbaum-Saunders distribution, a very flexible distribution for modeling different types of data (mainly lifetime data).

The book describes the most recent theoretical developments of this model, including properties, transformations and related distributions, lifetime analysis, and shape analysis. It discusses methods of inference based on uncensored and censored data, goodness-of-fit tests, and random number generation algorithms for the Birnbaum-Saunders distribution, also presenting existing and future applications.

• Introduces inference in the Birnbaum-Saunders distribution
• Provides a comprehensive review of the statistical theory and methodology of the Birnbaum-Distribution
• Discusses different applications of the Birnbaum-Saunders distribution
• Explains characterization and the lifetime analysis

Graduate engineering students, practicing engineers, quality engineers, reliability engineers, consultants

Chapter 1: Genesis of the Birnbaum–Saunders Distribution

• Abstract
• 1.1 Introduction
• 1.2 History
• 1.3 Fatigue, genesis, and derivation
• 1.4 Applications

Chapter 2: Characterizations of the Birnbaum–Saunders Distribution

• Abstract
• 2.1 Introduction
• 2.2 Probability functions and properties
• 2.3 Characteristic function and moments
• 2.4 Generation of random numbers

Chapter 3: Inference for the Birnbaum–Saunders Distribution

• Abstract
• 3.1 Introduction
• 3.2 Maximum likelihood estimation method
• 3.3 Moment estimation method
• 3.4 Graphical estimation method

Chapter 4: Modeling Based on the Birnbaum–Saunders Distribution

• Abstract
• 4.1 Introduction
• 4.2 The log-Birnbaum–Saunders distribution
• 4.3 Regression models
• 4.4 Diagnostic methods

Chapter 5: Goodness of Fit for the Birnbaum–Saunders Distribution

• Abstract
• 5.1 Introduction
• 5.2 Goodness of fit based on moments
• 5.3 Model selection
• 5.4 Probability plots

Chapter 6: Data Analyses with the Birnbaum–Saunders Distribution

• Abstract
• 6.1 Introduction
• 6.2 Data sets
• 6.3 Software
• 6.4 Modeling and diagnostics with real-world data