Abstract
Lan and Leemis (2008) introduced logistic-exponential (LE) distribution which has varied applications in lifetime modellings. In this article, we consider parametric bootstrap control charts (BCCs) for detecting a shift in the percentile of LE distribution in a process monitoring situation. Four parametric BCCs based on maximum likelihood method, method of least squares, method of Cramer-von-Mises and ` method of maximum product of spacings are used for monitoring percentiles of LE distribution. We perform simulations to see the performances of the proposed four BCCs with respect to average run length. Finally, one data set is analyzed to illustrate our results.
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