International Research Journal of Agricultural Economics and Statistics

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Variance Estimation Using Linear Combination of Non-Conventional Measures, Quartile Average and Deciles Mean


Affiliations
1 Division of Agricultural Statistics, SKUAST, Kashmir (J&K), India
     

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Use of auxiliary information in survey sampling plays important role in getting more precision for estimating population parameters. Thus it has now become indispensable to use auxiliary information, thus in this paper we propose new modified ratio estimators by using the auxiliary information of non conventional location measures, non conventional measures of dispersion, quartile average, decile mean and their linear combinations for estimating population variance. The properties associated with proposed estimators are assessed by mean square error, bias and compared with existing estimators. By this comparison we conclude that our proposed estimators are more efficient than the existing estimators. To support the theoretical results, numerical study is provided.

Keywords

Simple Random Sampling, Bias, Mean Square Error, Downtown’s Method, Deciles, Efficiency.
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  • Sumramani, J. and Kumarapandiyan, G. (2015).Generalized modified ratio type estimator for estimation of population variance. Sri-Lankan J. Appl. Statist.,16 (1): 69-90.

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  • Variance Estimation Using Linear Combination of Non-Conventional Measures, Quartile Average and Deciles Mean

Abstract Views: 233  |  PDF Views: 0

Authors

M. A. Bhat
Division of Agricultural Statistics, SKUAST, Kashmir (J&K), India
S. Maqbool
Division of Agricultural Statistics, SKUAST, Kashmir (J&K), India
S. A. Mir
Division of Agricultural Statistics, SKUAST, Kashmir (J&K), India

Abstract


Use of auxiliary information in survey sampling plays important role in getting more precision for estimating population parameters. Thus it has now become indispensable to use auxiliary information, thus in this paper we propose new modified ratio estimators by using the auxiliary information of non conventional location measures, non conventional measures of dispersion, quartile average, decile mean and their linear combinations for estimating population variance. The properties associated with proposed estimators are assessed by mean square error, bias and compared with existing estimators. By this comparison we conclude that our proposed estimators are more efficient than the existing estimators. To support the theoretical results, numerical study is provided.

Keywords


Simple Random Sampling, Bias, Mean Square Error, Downtown’s Method, Deciles, Efficiency.

References