Bayesian and Maximum Likelihood Estimation for Kumaraswamy Distribution Based on Ranked Set Sampling

摘要

In this paper, the estimation of the unknown parameters of the kumaraswamy distribution is considered using both simple random sampling (SRS) and ranked set sampling (RSS) techniques. The estimation is based on maximum likelihood estimation and Bayesian estimation methods. A simulation study is made to compare the resultant estimators in terms of their biases and mean square errors. The efficiency of the estimates made using ranked set sampling are also computed.