Improving Efficiency of Finite Population Distribution Function Using Twofold Auxiliary Information Based on Simple Random Sampling

The main purpose of this article has been suggested two modified ratio type estimators for estimation of finite population distribution function using auxiliary information under simple random sampling. Mathematical expressions such as Mean Square Error (MSE) and Bias are examined up to the first order approximation for all considered estimators in this article. For the ideal value of the kappa constant (K), the minimum MSE value for the recommended estimators has been found. Five actual data sets have been carried out to check the precision of the suggested estimators. The suggested estimators found to be superior and more efficient than the existing estimators for population distribution function. The theoretical and empirical comparisons are also conducted. Hypothetically, the proposed estimators perform better than the existing estimators.