An improved regression type mean estimator using redescending M-estimator
Keywords:
Robust Regression, Outliers, Redescending M-estimatorAbstract
In this article, a novel technique is presented for calculating the mean of a countable population using simple random sampling (SRS) in situations where there are outliers in the data. The proposed approach employs a robust regression type estimation method called re-descending M-estimation. To assess the effectiveness of the new method, the mean square error (MSE) equation is derived using a first-order approximation and compared against existing estimation methods. Furthermore, the percentage relative efficiency (PRE) of the proposed estimator is calculated in comparison to other estimators. Real-life data sets are employed to demonstrate the efficacy of the suggested approach. The results indicate that the proposed estimator outperforms other estimators in the literature.
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