Estimation based on Ranked Set Sampling for Farlie--Gumbel--Morgenstern Bivariate Weibull Distribution Parameters with an application to medical data

Abstract

In this article, we address the problem of estimating the parameters of Farlie-Gumbel-Morgenstern bivariate Weibull distribution using ranked set sample (RSS) design. The suggested estimators of the FGMBW distribution parameters are compared with their counterparts based on simple random sampling (SRS) via Monte Carlo simulations studies. An example of a real data set consists of times (in days) to the first and second recurrence of infection for 30 kidney patients is considered for illustration. It turns out that the RSS estimators results in an improvement in efficiency as compared to the simple random sampling estimators based on the same number of measured units for all cases considered in this study.