Entropy Estimation From Ranked Set Samples With Application to Test of Fit

Improved entropy based test of uniformity using ranked set samples

Ranked set sampling (RSS) is known to be superior to the traditional simple random sampling (SRS) in the sense that it often leads to more efficient inference procedures. Basic version of RSS has been extensively modified to come up with schemes resulting in more accurate estimators of the population attributes. Multistage ranked set sampling (MSRSS) is such a variation surpassing RSS. Entropy ...

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 ...

Improved Estimation from Ranked Set Sampling

Ranked set sampling is used when the measurement or quantification of units of the variable under study is difficult but the ranking of units of sets of small sizes can be done easily by an inexpensive method. Dell and Clutter (1972) showed that the sample mean based on ranked set sample is more efficient than the sample mean based on simple random sample with replacement sampling procedure for...

Quantile Estimation from Ranked Set Sampling Data

We consider estimation of quantiles when data are generated from ranked set sampling. A new estimator is proposed and is shown to have a smaller asymptotic variance for all distributions. It is also shown that the optimal sampling strategy is to select observations with one fixed rank from different ranked sets. Both the optimal rank and the relative efficiency gain with respect to simple rando...

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