Logarithmic type predictive estimators under simple random sampling

This study introduces a novel predictive estimation approach of the population mean based on logarithmic type estimators as predictor under simple random sampling. The bias and mean square error of the proffered predictive estimators are examined to the approximation of order one. The efficiency conditions are obtained and the performance of the proffered predictive estimators is examined regarding the contemporary predictive estimators existing till date. Further, a broad computational study is also administered utilizing few real and artificially rendered symmetric and asymmetric populations to exemplify the theoretical results.