Maximum Likelihood Estimator of the Location Parameter under Moving Extremes Ranked Set Sampling Design

• 作者: Wang-xue CHEN Chun-xian LONG Rui YANG Dong-sen YAO
• 来源期刊: 应用数学学报（英文版）
• 年，卷（期）: 2021,（1）
• 页码范围: 101-108
• 页数: 8页
• 语种: 英文

摘要

Cost effective sampling design is a problem of major concern in some experiments especially when the measurement of the characteristic of interest is costly or painful or time consuming.In the current paper,a modification of ranked set sampling(RSS)called moving extremes RSS(MERSS)is considered for the estimation of the location parameter for location family.A maximum likelihood estimator(MLE)of the location parameter for this family is studied and its properties are obtained.We prove that the MLE is an equivariant estimator under location transformation.In order to give more insight into the performance of MERSS with respect to(w.r.t.)simple random sampling(SRS),the asymptotic efficiency of the MLE using MERSS w.r.t.that using SRS is computed for some usual location distributions.The relative results show that the MLE using MERSS can be real competitors to the MLE using SRS.