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In study described in this article, we developed a memory type estimator for the population mean in stratified successive sampling. We used the past sample information together with the current sample information through hybrid exponentially weighted moving averages statistics. We have also used the information available on auxiliary variable to construct the proposed estimator. We studied the properties of the proposed estimator. Further, we examined the performance of the proposed estimator in comparison with conventional estimator of the population mean and the results are demonstrated by using the data set of simulation as well as natural population. After observing the auspicious findings, we suggest that the proposed estimator can be applied to solve real-life problems.
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