The traditional simple random sampling(SRS)design method is inefficient in many cases.Statisticians proposed some new designs to increase efficiency.In this paper,as a variation of moving extremes ranked set sampling(...The traditional simple random sampling(SRS)design method is inefficient in many cases.Statisticians proposed some new designs to increase efficiency.In this paper,as a variation of moving extremes ranked set sampling(MERSS),double MERSS(DMERSS)is proposed and its properties for estimating the population mean are considered.It turns out that,when the underlying distribution is symmetric,DMERSS gives unbiased estimators of the population mean.Also,it is found that DMERSS is more efficient than the SRS and MERSS methods for usual symmetric distributions(normal and uniform).For asymmetric distributions considered in this study,the DMERSS has a small bias and it is more efficient than SRS for usual asymmetric distribution(exponential)for small sample sizes.展开更多
The procedure of stratified double quartile ranked set sampling （SDQRSS） method is introduced to estimate the population mean. The SDQRSS is compared with the simple random sampling （SRS）, stratified ranked set sa...The procedure of stratified double quartile ranked set sampling （SDQRSS） method is introduced to estimate the population mean. The SDQRSS is compared with the simple random sampling （SRS）, stratified ranked set sampling （SRSS） and stratified simple random sampling （SSRS）. It is shown that SDQRSS estimator is an unbiased of the population mean and more efficient than SRS, SRSS and SSRS for symmetric and asymmetric distributions. In addition, by SDQRSS we can increase the efficiency of mean estimator for specific value of the sample size.展开更多
This paper presents some novel entropy estimators of a continuous random variable using simple random sampling(SRS),ranked set sampling(RSS),and double RSS(DRSS)schemes.The theoretical results of the proposed entropy ...This paper presents some novel entropy estimators of a continuous random variable using simple random sampling(SRS),ranked set sampling(RSS),and double RSS(DRSS)schemes.The theoretical results of the proposed entropy estimators are derived.The proposed entropy estimators are compared in terms of the bias and the root mean squared errors,theoretically and numerically,with the Vasicek O.[A test for normality based on sample entropy,J.R.Stat.Soc.B 38:54–59,1976.]entropy estimators using SRS,RSS,and DRSS schemes.It turns out that the new novel entropy estimators are substantially better than the existing Vasicek’s entropy estimators.展开更多
基金supported by the This research was supported by National Science Foundation of China(Grant Nos.12261036 and 11901236)Provincial Natural Science Foundation of Hunan(Grant No.2022JJ30469)Scientific Research Fund of Hunan Provincial Education Department(Grant No.21A0328)。
文摘The traditional simple random sampling(SRS)design method is inefficient in many cases.Statisticians proposed some new designs to increase efficiency.In this paper,as a variation of moving extremes ranked set sampling(MERSS),double MERSS(DMERSS)is proposed and its properties for estimating the population mean are considered.It turns out that,when the underlying distribution is symmetric,DMERSS gives unbiased estimators of the population mean.Also,it is found that DMERSS is more efficient than the SRS and MERSS methods for usual symmetric distributions(normal and uniform).For asymmetric distributions considered in this study,the DMERSS has a small bias and it is more efficient than SRS for usual asymmetric distribution(exponential)for small sample sizes.
文摘The procedure of stratified double quartile ranked set sampling （SDQRSS） method is introduced to estimate the population mean. The SDQRSS is compared with the simple random sampling （SRS）, stratified ranked set sampling （SRSS） and stratified simple random sampling （SSRS）. It is shown that SDQRSS estimator is an unbiased of the population mean and more efficient than SRS, SRSS and SSRS for symmetric and asymmetric distributions. In addition, by SDQRSS we can increase the efficiency of mean estimator for specific value of the sample size.
文摘This paper presents some novel entropy estimators of a continuous random variable using simple random sampling(SRS),ranked set sampling(RSS),and double RSS(DRSS)schemes.The theoretical results of the proposed entropy estimators are derived.The proposed entropy estimators are compared in terms of the bias and the root mean squared errors,theoretically and numerically,with the Vasicek O.[A test for normality based on sample entropy,J.R.Stat.Soc.B 38:54–59,1976.]entropy estimators using SRS,RSS,and DRSS schemes.It turns out that the new novel entropy estimators are substantially better than the existing Vasicek’s entropy estimators.
