Optimal Sample Size for the Birnbaum-Saunders Distribution under Decision Theory with Symmetric and Asymmetric Loss Functions

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Author(s):	Costa, Eliardo ^[1] ; Santos-Neto, Manoel ^[2] ; Leiva, Victor ^[3] Total Authors: 3
Affiliation:	^[1] Univ Fed Rio Grande do Norte, Dept Stat, Natal 59078-970, RN - Brazil ^[2] Univ Fed Campina Grande, Dept Stat, Campina Grande 58429-900, Paraiba - Brazil ^[3] Pontificia Univ Catolica Valparaiso, Sch Ind Engn, Valparaiso 2362807 - Chile Total Affiliations: 3
Document type:	Journal article
Source:	SYMMETRY-BASEL; v. 13, n. 6 JUN 2021.
Web of Science Citations:	1
Abstract
The fatigue-life or Birnbaum-Saunders distribution is an asymmetrical model that has been widely applied in several areas of science and mainly in reliability. Although diverse methodologies related to this distribution have been proposed, the problem of determining the optimal sample size when estimating its mean has not yet been studied. In this paper, we derive a methodology to determine the optimal sample size under a decision-theoretic approach. In this approach, we consider symmetric and asymmetric loss functions for point and interval inference. Computational tools in the R language were implemented to use this methodology in practice. An illustrative example with real data is also provided to show potential applications. (AU)

FAPESP's process:	13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:	Francisco Louzada Neto
Support Opportunities:	Research Grants - Research, Innovation and Dissemination Centers - RIDC