ON THE HYBRIDIZED LINEAR-RATIO ESTIMATOR FOR SUCCESSIVE SAMPLING ON TWO OCCASIONS
Abstract
Information on rate of changes in longitudinal surveys with certain types of population can robustly considered only by Successive sampling in estimate population parameters. Therefore, this study proposed a more efficient estimator technique in successive sampling schemes to determine the population estimates of the two occasions. The proposed estimator was obtained over mathematical expectation and statistical assumptions to derived an unbiased estimate of mean ( ), minimum variance ( ) and Relative efficiency comparison (REC). A Real-life data were used to validate the expression in the study. The data were last two population census conducted in Nigeria in 1991 and 2006 respectively by National Population Commission (NPC). The findings of the study include a proposed estimator obtained by hybridization of linear and ratio estimator, mathematical estimations of the mean in first and second occasions, minimum variance with maximum precision and relative gain in efficiency of the four estimators; ESEst, EREst, ELEst and PHLREst derived; estimates of change and sum of the population parameters for the two occasions were derived and the estimates of change achieved minimum variance and maximum efficiency when correlation coefficient = 1.0 and proportion matched = 0.2. The study concluded that the proposed hybridized linear-ratio estimator is more efficient than the existing ones in term of precision. Moreover, these theoretical findings are certified by numerical illustration with the real-life data. Therefore, the proposed estimator is recommended for use in successive sampling scheme.
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