Failure rate of birnbaum–saunders distributions: Shape, change-point, estimation and robustness

Emilia Athayde, Assis Azevedo, Michelli Barros, Víctor Leiva

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)301-328
Number of pages28
JournalBrazilian Journal of Probability and Statistics
Volume33
Issue number2
DOIs
StatePublished - May 2019

Keywords

  • Bootstrapping
  • Likelihood-based methods
  • Logistic
  • Monte Carlo simulation
  • Normal and Student-t distributions
  • R computer language

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