An improved class of estimators for estimation of population distribution functions under stratified random sampling
Sohaib Ahmad, Javid Shabbir, Walid Emam, Erum Zahid, Muhammad Aamir, Mohd Khalid, Malik Muhammad Anas
Abstract
The main objective of the current study is to suggest an enhanced family of log ratio-exponential type estimators for population distribution function (DF) using auxiliary information under stratified random sampling. Putting different choices in our suggested generalized class of estimators, we found some Specific estimators. The bias and MSE expressions of the estimators have been approximated up to the first order. By using the actual and simulated data sets, we measured the performance of estimators. Based on the results, the suggested estimators for DF show better performance as compared to the preliminary estimators considered here. The suggested estimators have a advanced efficiency than the other estimators examined with the estimators F ¯ ˆ l o g P R ( s t ) 2 , and F ¯ ˆ l o g P R ( s t ) 4 for both the actual and simulated data sets. The magnitude of the improvement in efficiency is noteworthy, indicating the superiority of the proposed estimators in terms of MSE.