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Best Linear Unbiased Estimators of Location and Scale ranked set Parameters under moving extremes sampling Design

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Acta Mathematicae Applicatae Sinica 2023年第2期39卷 222-231页

作者： Yan-fei DONG Wang-xue CHEN Min-yu XIE Department of Mathematics and Statistics Jishou UniversityJishou 416000China Department of Mathematics and Statistics Central China Normal UniversityWuhan 430079China

In the current paper,the best linear unbiased estimators(BLUEs)of location and scale parameters from location-scale family will be respectively proposed in cases when one parameter is known and when both are unknown under moving extremes ranked set sampling(MERSS).Explicit mathematical expressions of these estimators and their variances are derived.Their relative efficiencies with respect to the minimum variance unbiased estimators(MVUEs)under simple random sampling(SRS)are compared for the cases of some usual distributions.The numerical results show that the BLUEs under MERSS are significantly more efficient than the MVUEs under SRS.

关键词： location-scale parameters best linear unbiased estimator moving extremes ranked set sampling

Maximum Likelihood Estimator of the Location Parameter under moving extremes ranked set sampling Design

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Acta Mathematicae Applicatae Sinica 2021年第1期37卷 101-108页

作者： Wang-xue CHEN Chun-xian LONG Rui YANG Dong-sen YAO Department of Mathematics and Statistics Jishou UniversityJishou 416000China

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.***.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.

关键词： ranked set sampling moving extremes ranked set sampling maximum Likelihood estimator equivariant estimator fisher information number

Fisher Information in moving Extreme ranked set sampling with Application to Parameter Estimation

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Journal of Systems Science & Complexity 2022年第1期35卷 361-372页

作者： YAO Dongsen CHEN Wangxue YANG Rui LONG Chunxian Department of Mathematics and Statistics Jishou UniversityJishou 416000China

In statistical parameter estimation problems,how well the parameters are estimated largely depends on the sampling design used.In the current paper,a modification of ranked set sampling called moving extremes ranked set sampling(MERSS)is considered for the Fisher information matrix for the location-scale family.The Fisher information matrix for this model are respectively derived under simple random sampling and MERSS.In order to give more insight into the performance of MERSS with respect to simple random sampling,the Fisher information matrix for usual locationscale distributions are respectively computed under the two sampling.The numerical results show that MERSS provides more information than simple random sampling in parametric inference.

关键词： Fisher information matrix location-scale family moving extremes ranked set sampling