The Birnbaum-Saunders Distribution

Nonfiction, Science & Nature, Mathematics, Statistics
Cover of the book The Birnbaum-Saunders Distribution by Victor Leiva, Elsevier Science
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Author: Victor Leiva ISBN: 9780128038277
Publisher: Elsevier Science Publication: October 26, 2015
Imprint: Academic Press Language: English
Author: Victor Leiva
ISBN: 9780128038277
Publisher: Elsevier Science
Publication: October 26, 2015
Imprint: Academic Press
Language: English
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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, 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.

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