Dynamic reliability estimation in a rank-based design

Ranked set sampling RSS is a data collection method that allows us to direct attention toward measurements of more representative sample units. This article deals with estimating a time-dependent reliability measure under a generalization of the RSS. Some results concerning optimal properties of the proposed estimator are presented. Monte Carlo simulation is employed to assess performance of the estimator. A sport data set is finally analyzed.Ranked set sampling RSS is a data collection method that allows us to direct attention toward measurements of more representative sample units. This article deals with estimating a time-dependent reliability measure under a generalization of the RSS. Some results concerning optimal properties of the proposed estimator are presented. Monte Carlo simulation is employed to assess performance of the estimator. A sport data set is finally analyzed

Efficient Estimation of Cumulative Distribution Function Using Moving Extreme Ranked Set Sampling With Application to Reliability

In this article, we consider the problem of estimating cumulative distribution function (CDF) and a reliability parameter using moving extreme ranked set sampling (MERSS). Two different CDF estimators are described and compared with their competitors in simple random sampling (SRS) and ranked set sampling (RSS). It turns out the CDF estimators in MERSS can be more efficient than their competitors in SRS and RSS at a point in a particular tail of the distribution when the quality of rankings is sufficiently good. Motivated by this efficiency gain, we develop some estimators for the stress-strength probability using MERSS. The suggested estimators are then compared with their counterparts in the literature via Monte Carlo simulation. Finally, a real dataset is used to show the applicability of the developed procedures

Smooth estimation of a reliability function in ranked set sampling

<p>The authors develop a kernel-based estimator of a dynamic reliability measure for use with independent ranked set samples. The estimator is in the form of a ratio, whose numerator and denominator are shown to outperform their rivals based on simple random samples. Some asymptotic properties about the proposed estimator are also established. Simulation studies reveal finite-sample properties of the estimator. The technique is finally applied on an agricultural data set.</p

Vacancy effects on the mechanical behavior of B2-FeAl intermetallics

The present work addresses the impact of quenched-in thermal vacancies on the mechanical properties of B2 iron aluminides. For this reason different binary Fe-Al alloys with different histories of heat treatment were indented at room temperature. The contributions of mono- and bi-vacancies in addition to triple defects on the elastic, plastic and elastic-plastic transition were evaluated using nanoindentation technique. In the samples containing bi-vacancies, the increase of the hardness was much more pronounced compared to the mono-vacancies