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This paper examines a class of regression estimator with cum-dual product estimator as intercept for estimating the mean of the study variable Y using auxiliary variable X. We obtained the bias and the mean square error (MSE) of the proposed estimator. We also obtained MSE of its asymptotically optimum estimator (AOE). Theoretical and numerical validation of the proposed estimator was done to show itβs superiority over the usual simple random sampling estimator and ratio estimator, product estimator, cum-dual ratio and product estimator. It was found that the asymptotic optimal value of the proposed estimator performed better than other competing estimators and performed in exactly the same way as the regression estimator, when compared with the usual simple random estimator for estimating the average sleeping hours of undergraduate students of the department of statistics,
N.A. Adegoke. 2015. "A Class of Regression Estimator with Cum-Dual Product Estimator as Intercept". Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 15 (GJSFR Volume 15 Issue F3).
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
v1.2
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Total Score: 102
Country: Nigeria
Subject: Global Journal of Science Frontier Research - F: Mathematics & Decision
Authors: F.B. Adebola, N.A. Adegoke (PhD/Dr. count: 0)
View Count (all-time): 330
Total Views (Real + Logic): 913
Total Downloads (simulated): 68
Publish Date: 2015 04, Wed
Monthly Totals (Real + Logic):
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