Improved Class of Ratio Estimators for Finite Population Variance

1
Audu Ahmed
Audu Ahmed
2
Adedayo Amos Adewara
Adedayo Amos Adewara
3
Ran Vijay Kumar Singh
Ran Vijay Kumar Singh
1 Usmanu Danfodiyo University Sokoto, Nigeria

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In this paper, we have suggested a class of improved ratio estimators for finite population variance. The proposed class of estimators is obtained by transforming both the sample variances of study and auxiliary variables. The MSE of the proposed estimators have been obtained and the conditions for their efficiency over some existing variance estimators have been established. The present family of finite variance estimator, having obtaining the optimal values of the constants, exhibit significant improvement over the estimators considered in the study. The empirical study is also conducted to corroborate the theoretical results and the results show that the proposed class of estimators is more efficient.

17 Cites in Articles

References

  1. A Adewara,R Singh,M Kumar (2012). On efficiency of some ratio estimators in double sampling design using some existing agricultural data.
  2. M Ahmed,W Dayyeh,A Hurairah (2003). On some Ratio and Regression Estimators for the Finite Population Variance in Two Phase Sampling.
  3. S Gupta,J Shabbir (2008). Variance estimation in simple random sampling using auxiliary information.
  4. C Isaki (1983). Variance estimation using auxiliary information.
  5. C Kadilar,H Cingi (2006). Ratio estimators for population variance in simple and stratified sampling.
  6. Cem Kadilar,Hulya Cingi (2007). Improvement in Variance Estimation in Simple Random Sampling.
  7. A Sanaullah,H Khan,A Ali,R Singh (2012). Improved ratio-type estimators in survey sampling.
  8. Rajesh Singh,Mukesh Kumar,Florentin Smarandache (2007). ALMOST UNBIASED ESTIMATOR FOR ESTIMATING POPULATION MEAN USING KNOWN VALUE OF SOME POPULATION PARAMETER(S).
  9. Viplav Singh,Rajesh Singh (2011). A Generalised Family of Estimator for Estimating Unknown Variance Using Two Auxiliary Variables.
  10. H Singh,R Solanki (2013). A new procedure for variance estimation in simple random sampling using auxiliary information.
  11. Housila Singh,Gajendra Vishwakarma (2008). Some Families of Estimators of Variance of Stratified Random Sample Mean Using Auxiliary Information.
  12. R Solanki,H Singh (2013). An improved class of estimators for the population variance.
  13. J Subramani,G Kumarapandiyan (2012). Variance Estimation Using Quartiles and their Functions of an Auxiliary Variable.
  14. L Upadhyaya,H Singh (1999). An estimator for population variance that utilizes the kurtosis of an auxiliary variable in sample surveys.
  15. S Yadav,C Kadilar (2013). Improved exponential type ratio estimator of population variance.
  16. S Yadav,C Kadilar (2013). Improved class of ratio and product estimators.
  17. (2016). Improved Class of Ratio Estimators for Finite Population Variance.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Audu Ahmed. 2016. \u201cImproved Class of Ratio Estimators for Finite Population Variance\u201d. Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 16 (GJSFR Volume 16 Issue F2): .

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GJSFR Volume 16 Issue F2
Pg. 17- 24
Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

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GJSFR-F Classification: MSC 2010: 00A05
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v1.2

Issue date

April 14, 2016

Language

English

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In this paper, we have suggested a class of improved ratio estimators for finite population variance. The proposed class of estimators is obtained by transforming both the sample variances of study and auxiliary variables. The MSE of the proposed estimators have been obtained and the conditions for their efficiency over some existing variance estimators have been established. The present family of finite variance estimator, having obtaining the optimal values of the constants, exhibit significant improvement over the estimators considered in the study. The empirical study is also conducted to corroborate the theoretical results and the results show that the proposed class of estimators is more efficient.

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Improved Class of Ratio Estimators for Finite Population Variance

Audu Ahmed
Audu Ahmed Usmanu Danfodiyo University Sokoto, Nigeria
Adedayo Amos Adewara
Adedayo Amos Adewara
Ran Vijay Kumar Singh
Ran Vijay Kumar Singh

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