Bootstrap prediction intervals for the Birnbaum-Saunders distribution

Ming Che Lu, Dong Shang Chang

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


The Birnbaum-Saunders distribution has been recognized as a versatile failure time model. However, it is not widely used in process control as some of its important characteristics have not been obtained. In this paper, we utilize the bootstrap method to construct a prediction interval for future observations from a Birnbaum-Saunders distribution. Monte Carlo simulations are carried out to evaluate the performance of the proposed procedure. The results reveal that the bootstrap intervals are satisfied with desired coverage probabilities and average lengths as sample size n is at least 30.

Original languageEnglish
Pages (from-to)1213-1216
Number of pages4
JournalMicroelectronics Reliability
Issue number8
StatePublished - Aug 1997


Dive into the research topics of 'Bootstrap prediction intervals for the Birnbaum-Saunders distribution'. Together they form a unique fingerprint.

Cite this