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New class of estimators for enhanced estimation of average production of peppermint yield utilising known auxiliary variable

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  • S.K. Yadav
  • Dinesh K. Sharma
  • Kate Brown

Abstract

The arithmetic mean is the best measure of central tendency for a homogenous population for the characteristics under study. Estimation can be improved by including auxiliary information and various estimators have been suggested in the literature. In this paper, a new class of estimators using known auxiliary parameters for estimation of the average yield of peppermint oil is suggested. The proposed estimator's sampling properties, the bias and mean squared error (MSE) up to the approximation of first order are studied. The suggested estimator is compared theoretically to some existing estimators of population mean that an auxiliary variable. The theoretical efficiency conditions are verified using real primary data collected from the Siddaur Block of Barabanki District at Uttar Pradesh State (India). The performances of various estimators are judged from their calculated MSEs using this primary data.

Suggested Citation

  • S.K. Yadav & Dinesh K. Sharma & Kate Brown, 2021. "New class of estimators for enhanced estimation of average production of peppermint yield utilising known auxiliary variable," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 20(2), pages 281-295.
    • Handle: RePEc:ids:ijmore:v:20:y:2021:i:2:p:281-295
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