The Birnbaum-saunders Distribution

Paperback | October 22, 2015

byVictor LeivaEditorVictor Leiva

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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

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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, transformation...

Format:PaperbackDimensions:154 pages, 8.75 × 6.35 × 0.68 inPublished:October 22, 2015Publisher:Academic PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0128037695

ISBN - 13:9780128037690

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Table of Contents

1 Genesis

1.1 Introduction

1.2 History

1.3 Fatigue, genesis and derivation

1.4 Applications

2 Characterizations

2.1 Introduction

2.2 Probability functions and properties

2.3 Characteristic function and moments

2.4 Generation of random numbers

3 Inference

3.1 Introduction

3.2 Maximum likelihood estimation method

3.3 Moment estimation method

3.4 Graphical estimation method

4 Modelling

4.1 Introduction

4.2 The logarithmic Birnbaum-Saunders distribution

4.3 Regression models

4.4 Diagnostics methods

5 Data analysis and fitting

5.1 Introduction

5.2 Goodness-of-fit based on moments

5.3 Goodness-of-fit based on probability plots

5.4 Data analysis