Bayes Estimation of the Mean of Normal Distribution Using Moving Extreme Ranked Set Sampling

Estimation of Variance of Normal Distribution using Ranked Set Sampling

Introduction     In some biological, environmental or ecological studies, there are situations in which obtaining exact measurements of sample units are much harder than ranking them in a set of small size without referring to their precise values. In these situations, ranked set sampling (RSS), proposed by McIntyre (1952), can be regarded as an alternative to the usual simple random sampling ...

Estimation Using Bivariate Extreme Ranked Set Sampling With Application To The Bivariate Normal Distribution

Design Based Estimation of Finite Population Mean in Ranked Set Sampling

Abstract. This Article introduce method of ranked set sampling with replacement (RSSWR) in finite population and express how to computing samples of inclusion probability for this method. The Horvitz-Thompson and Hansen-Hurwtz estimators using auxiliary variables introduce for this design and use 2011-12 Urban Households Income and Income and Expenditure survey data, gathered for Tehran by stat...

Test of the Correlation Coefficient in Bivariate Normal Populations Using Ranked Set Sampling

Ranked Set Sampling (RSS) is a statistical method for data collection that leads to more efficient estimators than competitors based on Simple Random Sampling (SRS). We consider testing the correlation coefficient of bivariate normal distribution based on Bivariate RSS (BVRSS). Under one-sided and two-sided alternatives, we show that the new tests based on BVRSS are more powerful than the usua...

Extreme ranked set sampling: A comparison with regression and ranked set sampling estimators

Ranked set sampling (RSS) assumed perfect ranking i.e. there will be no errors in ranking the units with respect to the variable of interest. In fact for most practical applications, it is not easy to rank the units without errors in ranking. There will be a loss in efficiency, i.e. RSS will give a larger variance due to the errors in ranking the units. To reduce the errors in ranking in estima...