MODIFIKASI PENAKSIR PRODUK MENGGUNAKAN KOEFISIEN REGRESI ROBUST PADA SAMPEL ACAK SEDERHANA
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Date
2020-10
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Abstract
The product estimator being discussed is the product estimator for the average population
in a simple random sampling using the robust regression coefficient. Robust regression
being discussed uses the Least Trimmed Square (LTS) estimation method to estimate the
slope coefficient. It is found that all three estimators are biased estimators. Then, the
Mean Square Error (MSE) of the three estimators is compared to find the efficient
estimator. It is found that an estimator that uses a combination of robust regression
coefficient and kurtosis coefficient turns out to be the most efficient than other estimators
when conditions are satisfied.
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Keywords
Product estimator, simple random sampling, robust regression, Mean Square Error, coefficient of kurtosis