Inferences on a Scale Parameter of Bivariate Rayleigh Distribution by Ranked Set Sampling

Estimation of a parameter of Morgenstern type bivariate exponential distribution by ranked set sampling

Ranked set sampling is applicable whenever ranking of a set of sampling units can be done easily by a judgement method or based on the measurement of an auxiliary variable on the units selected. In this work, we consider ranked set sampling, in which ranking of units are done based on measurements made on an easily and exactly measurable auxiliary variable X which is correlated with the study v...

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 of Parameters of Morgenstern Type Bivariate Logistic Distribution by Ranked Set Sampling

The concept of ranked set sampling was first introduced by McIntyre (1952) as a process of improving the precision of the sample mean as an estimator of the population mean. This is applicable whenever ranking of a set of sampling units can be done easily by a judgement method see, Chen et al. (2004). Ranking by judgement method is not recommendable if the judgement method is not mathematically...

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

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...