The Birnbaum-saunders Distribution by Victor LeivaThe Birnbaum-saunders Distribution by Victor Leiva

The Birnbaum-saunders Distribution

byVictor LeivaEditorVictor Leiva

Paperback | October 22, 2015

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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
Title:The Birnbaum-saunders DistributionFormat: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


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