A New Exponential Ratio-Type Estimator for Population Mean Using Two Auxiliary Variables in Double Sampling

@article{1715360,
      author = {Faweya, Olanrewaju, Abifade, Victor Oluwatobi, Akinyemi, Oluwadare, Ayodele, Oluwasola Joshua, Oyinloye, Adedeji Adigun},
      title = {A New Exponential Ratio-Type Estimator for Population Mean Using Two Auxiliary Variables in Double Sampling},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {9},
      pages = {1795-1799},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1715360.pdf},
      abstract = {In this study, a new exponential ratio-type estimator for estimating the population mean using two auxiliary variables in double sampling is proposed. The bias and mean squared error (MSE) of the proposed estimator are derived. The efficiency of the proposed estimator is compared theoretically with some existing estimators such as the usual sample mean estimator, the classical ratio estimator, and other exponential estimators. An empirical study using real-life data is conducted to examine the performance of the estimator. The results indicate that the proposed estimator has the smallest mean square error and the highest relative efficiency among the estimators considered. Hence, the estimator is recommended for practical applications in survey sampling where auxiliary information is available.},
      keywords = {Double Sampling, Auxiliary Variable, Exponential Estimator, Ratio Estimator, Mean Square Error.},
      month = {March},
      doi = {https://doi.org/10.64388/IREV9I9-1715360}
  }