Estimate of Population Variance by Introducing Gini’s Mean Difference as Auxiliary Information
M. A. Bhat *
Division of Agricultural Statistics, Sher-e-Kashmir University of Agricultural Sciences and Technology, SKUAST-Kashmir (190025), India.
S. Maqbool
Faculty of Horticulture, Sher-e-Kashmir University of Agricultural Sciences and Technology, SKUAST-Kashmir (190025), India.
S. A. Mir
Faculty of Horticulture, Sher-e-Kashmir University of Agricultural Sciences and Technology, SKUAST-Kashmir (190025), India.
T. A. Raja
Faculty of Horticulture, Sher-e-Kashmir University of Agricultural Sciences and Technology, SKUAST-Kashmir (190025), India.
Ab. Rauf
Faculty of Horticulture, Sher-e-Kashmir University of Agricultural Sciences and Technology, SKUAST-Kashmir (190025), India.
N. A. Sofi
Faculty of Horticulture, Sher-e-Kashmir University of Agricultural Sciences and Technology, SKUAST-Kashmir (190025), India.
Immad A. Shah
Faculty of Horticulture, Sher-e-Kashmir University of Agricultural Sciences and Technology, SKUAST-Kashmir (190025), India.
*Author to whom correspondence should be addressed.
Abstract
In this study we have introduced a new reliable and robust ratio estimator for estimating the population variance by utilizing the auxiliary information as Gini’s mean difference. Efficiency conditions along with bias and mean square error has been worked out through a numerical demonstration under which proposed estimator have proven better than the existing estimators under consideration.
Keywords: Ratio estimator, Gini’s mean difference, SRSWOR, MSE, bias and efficiency