Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/59401

TitleFailure rate of Birnbaum–Saunders distributions: shape, change-point, estimation and robustness
Author(s)Athayde, Emilia
Azevedo, Assis
Barros, Michelli
Leiva, Víctor
KeywordsLikelihood-based methods
Bootstrapping
Student-t distribution
R computer language
Logistic distribution
Monte Carlo simulation
Issue dateMar-2019
JournalBrazilian Journal of Probability and Statistics
Abstract(s)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.
TypeArticle
URIhttp://hdl.handle.net/1822/59401
DOI10.1214/17-BJPS389
ISSN0103-0752
e-ISSN0103-0752
Publisher versionhttps://doi.org/10.1214/17-BJPS389
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CMAT - Artigos em revistas com arbitragem / Papers in peer review journals

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