Estimation of population proportion using concomitant based ranked set sampling

Abstract

This paper considers the concomitant based double ranked set sampling (CDRSS) for estimating the population proportion and compares with existing concomitant based ranked set sampling (CRSS) and simple random sampling (SRS) schemes. Moreover, taking into account information on a single concomitant variable, we also develop ratio-and exponential-type estimators, along with their biases and mean square errors (MSEs) up to first order of approximation, for precisely estimating the population proportion using CRSS and CDRSS schemes. The advantages of the ratio-and exponential-type estimators over SRS estimator are investigated in terms of the relative precision. A real data application is also given to support the theory.