Ratio estimators for ranked set sampling in the presence of tie information

Abstract

In this article, we study the situation of observations whose ranks cannot be determined for the auxiliary variable in the Ranked Set Sampling (RSS) method. Therefore, we examine the case of tie information for ratio estimators of the population mean. We propose a new exponential ratio estimator using the modified isotonic estimator for this situation. Simulation results show that the proposed estimator is more efficient than the other estimators in literature. In addition, when we examine the recent COVID-19 pandemic situation, we see that the data is suitable for this structure. We can also see from the real data that the proposed estimator gives better results.