Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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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.
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): .
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Total Score: 103
Country: Nigeria
Subject: Global Journal of Science Frontier Research - F: Mathematics & Decision
Authors: Audu Ahmed, Adedayo Amos Adewara, Ran Vijay Kumar Singh (PhD/Dr. count: 0)
View Count (all-time): 107
Total Views (Real + Logic): 3755
Total Downloads (simulated): 1997
Publish Date: 2016 04, Thu
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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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