Abstract
This study investigates, for the first time, the product of spacing estimation of the modified Kies exponential distribution parameters as well as the acceleration factor using constant-stress partially accelerated life tests under the Type-II censoring scheme. Besides this approach, the conventional maximum likelihood method is also considered. The point estimates and the approximate confidence intervals of the unknown parameters are obtained using the two methods. In addition, two parametric bootstrap confidence intervals are discussed based on both estimation methods. Extensive simulation studies are conducted by considering different censoring schemes to examine the efficiency of each estimation method. Finally, two real data sets for oil breakdown times of insulating fluid and minority electron mobility are analyzed to show the applicability of the different methods. Moreover, the reliability function and the mean time-to-failure under the normal use condition are estimated using both methods. Based on Monte Carlo simulation outcomes and real data analysis, we recommend using the maximum product of spacing to evaluate both the point and interval estimates for the modified Kies exponential distribution parameters in the presence of constant-stress partially accelerated Type-II censored data.
Highlights
Academic Editor: Ioannis S.Many current manufactured products are highly reliable because of competitiveness between manufacturers
Using the same approach as the maximum likelihood (ML) estimation method and from large sample theory, we constructed the approximate confidence intervals (ACIs) for the unknown parameters based on the MPS estimators (MPSEs)
Merging all the earlier results, we suggest using the maximum product of spacing (MPS) estimation method to estimate the parameters of the modified Kies exponential (MKE) distribution based on CSPALT and Type-II
Summary
Besides the flexibility of the PDF and HRF of this distribution, one of the most desirable distributional properties is the simple closed-form cumulative distribution function (CDF) In this case, the distribution is suitable for use in different areas, such as life testing, reliability analysis, medical studies and survival analysis. The researcher may not always obtain a complete sample of failure times for all examination units in life reliability analysis and testing investigations Data gained from such tests are described as censored data. There are many censoring schemes in life testing, and the foremost familiar censoring schemes are Type-I and Type-II censoring (see, for more details, Lawless [19]) Motivated by such causes, as stated before, studying the MKE distribution under CSPALT in the presence of Type-II censored data is of considerable interest.
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