Inference for the common mean of several Birnbaum–Saunders populations

Xu Guo, Hecheng Wu, Gaorong Li, Qiuyue Li

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The Birnbaum–Saunders distribution is a widely used distribution in reliability applications to model failure times. For several samples from possible different Birnbaum–Saunders distributions, if their means can be considered as the same, it is of importance to make inference for the common mean. This paper presents procedures for interval estimation and hypothesis testing for the common mean of several Birnbaum–Saunders populations. The proposed approaches are hybrids between the generalized inference method and the large sample theory. Some simulation results are conducted to present the performance of the proposed approaches. The simulation results indicate that our proposed approaches perform well. Finally, the proposed approaches are applied to analyze a real example on the fatigue life of 6061-T6 aluminum coupons for illustration.

Original languageEnglish (US)
Pages (from-to)941-954
Number of pages14
JournalJournal of Applied Statistics
Volume44
Issue number5
DOIs
StatePublished - Apr 4 2017

Fingerprint

Birnbaum-Saunders Distribution
Common Mean
Large Sample Theory
Interval Estimation
Failure Time
Fatigue Life
Hypothesis Testing
Aluminum
Simulation
Inference
Model

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

Guo, Xu ; Wu, Hecheng ; Li, Gaorong ; Li, Qiuyue. / Inference for the common mean of several Birnbaum–Saunders populations. In: Journal of Applied Statistics. 2017 ; Vol. 44, No. 5. pp. 941-954.
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Inference for the common mean of several Birnbaum–Saunders populations. / Guo, Xu; Wu, Hecheng; Li, Gaorong; Li, Qiuyue.

In: Journal of Applied Statistics, Vol. 44, No. 5, 04.04.2017, p. 941-954.

Research output: Contribution to journalArticle

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