CD Skripsi
Modifikasi Penaksir Produk Menggunakan Koefisisen Regresi Robust Pada Sampel Acak Sederhana
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 compered to find the most 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.
Keywords: Product estimator, simple random sampling, robust regression, Mean
Square Error, coefficient of kurtosis
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