This paper introduces a new sampling design in a finite population setting, where potential
sampling units have a wealth of auxiliary information that can be used to rank them into …

This paper draws statistical inference for population characteristics using two-stage cluster
samples. Cluster samples in each stage are constructed using ranked set sample (RSS) …

In a finite population setting, this paper considers a partially rank ordered set (PROS)
sampling design. The PROS design selects a simple random sample (SRS) of M units …

This paper develops statistical inference based on a post-stratified probability-proportional-
to-size (pp) sample from a finite population. A pp sample selects the sample units with …

We derive recursive algorithms for computing first-order and second-order inclusion
probabilities for ranked-set sampling from a finite population. These algorithms make it …

Inference for the system reliability R is one of the most popular problems in the areas of
engineering, statistics, biostatistics and etc. Therefore, there exist considerable numbers of …

This paper develops statistical inference based on super population model in a finite
population setting using ranked set samples (RSS). The samples are constructed without …

This paper introduces new estimators for population total and mean in a finite population
setting, where ranks (or approximate ranks) of population units are available before …

Abstract Ranked Set Sampling (RSS) is preferred to Simple Random Sampling (SRS) when
measuring an observation is expensive or time-consuming, while ranking small subset of …

This paper considers the ratio estimator in a finite population setting in a ranked set
sampling (RSS) design, where the sample is constructed either with or without replacement …