排序集抽样下Rayleigh分布的参数估计

Parametric Estimator of Rayleigh Distribution under Ranked Set Sampling

当研究目标的实际测量具有不可修复的破坏性或耗资巨大时,有效的抽样设计将是一项重要的研究课题.在统计推断方面,排序集抽样(RSS)被视为一种有效的收集数据的方式.文章分别在简单随机抽样(SRS)和RSS下研究了Rayleigh分布中参数的无偏估计,最优线性无偏估计(BLUE),极大似然估计(MLE)和修正MLE.数值结果显示RSS估计比SRS估计更有效.

Cost effective sampling will be an important research problem in some experiments especially when the measurement of the characteristic of interest is costly or painful.Ranked set sampling(RSS)is now regarded as an effective tool in statistical inference.In this article,unbiased estimator,best linear unbiased estimator(BLUE),maximum likelihood estimator(MLE)and modified MLE of the parameter of Rayleigh distribution will be respectively studied under simple random sampling(SRS)and RSS.The numerical results show that these estimators under RSS are significantly more efficient than the ones under SRS.