4.0 Article

Failure rate of Birnbaum-Saunders distributions: Shape, change-point, estimation and robustness

Journal

BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS
Volume 33, Issue 2, Pages 301-328

Publisher

BRAZILIAN STATISTICAL ASSOCIATION
DOI: 10.1214/17-BJPS389

Keywords

Bootstrapping; likelihood-based methods; logistic; normal and Student-t distributions; Monte Carlo simulation; R computer language

Funding

  1. Research Centre of Mathematics of the University of Minho
  2. Fundacao para a Ciencia e a Tecnologia [UID/MAT/00013/2013]
  3. Brazilian Council for Scientific and Technological Development (CNPq)
  4. Chilean Council for Scientific and Technology Research (Conicyt) [FONDECYT 1160868]

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The Birnbaum-Saunders (BS) distribution has been largely studied and applied. A random variable with BS distribution is a transformation of another random variable with standard normal distribution. Generalized BS distributions are obtained when the normally distributed random variable is replaced by another symmetrically distributed random variable. This allows us to obtain a wide class of positively skewed models with lighter and heavier tails than the BS model. Its failure rate admits several shapes, including the unimodal case, with its change-point being able to be used for different purposes. For example, to establish the reduction in a dose, and then in the cost of the medical treatment. We analyze the failure rates of generalized BS distributions obtained by the logistic, normal and Student-t distributions, considering their shape and change-point, estimating them, evaluating their robustness, assessing their performance by simulations, and applying the results to real data from different areas.

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