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Bootstrap confidence intervals for industrial recurrent event data. (English) Zbl 1329.62155

Summary: Industrial recurrent event data where an event of interest can be observed more than once in a single sample unit are presented in several areas, such as engineering, manufacturing and industrial reliability. Such type of data provide information about the number of events, time to their occurrence and also their costs. W. Nelson [Technometrics 37, No. 2, 147–157 (1995; Zbl 0822.62084)] presents a methodology to obtain asymptotic confidence intervals for the cost and the number of cumulative recurrent events. Although this is a standard procedure, it can not perform well in some situations, in particular when the sample size available is small. In this context, computer-intensive methods such as bootstrap can be used to construct confidence intervals. In this paper, we propose a technique based on the bootstrap method to have interval estimates for the cost and the number of cumulative events. One of the advantages of the proposed methodology is the possibility for its application in several areas and its easy computational implementation. In addition, it can be a better alternative than asymptotic-based methods to calculate confidence intervals, according to some Monte Carlo simulations. An example from the engineering area illustrates the methodology.

MSC:

62F25 Parametric tolerance and confidence regions
62F40 Bootstrap, jackknife and other resampling methods
62P30 Applications of statistics in engineering and industry; control charts

Citations:

Zbl 0822.62084

Software:

bootstrap
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Full Text: DOI Link

References:

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