Kebutuhan Rumah Sederhana di Kabupaten Jember dengan Robust Small Area Estimation
Date
2017-02-02Author
MURTINASARI, Frida
HADI, Alfian Futuhul
ANGGRAENI, Dian
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Show full item recordAbstract
SAE (Small Area Estimation) is often used by researchers, especially statisticians to estimate parameters of a
subpopulation which has a small sample size. Empirical Best Linear Unbiased Prediction (EBLUP) is one of the
indirect estimation methods in Small Area Estimation. The presence of outliers in the data can not guarantee that
these methods yield precise predictions . Robust regression is one approach that is used in the model Small Area
Estimation. Robust approach in estimating such a small area known as the Robust Small Area Estimation.
Robust Small Area Estimation divided into several approaches. It calls Maximum Likelihood and M- Estimation. From the result, Robust Small Area Estimation with M-Estimation has the smallest RMSE than
others. The value is 1473.7 (with outliers) and 1279.6 (without outlier). In addition the research also indicated
that REBLUP with M-Estimation more robust to outliers. It causes the RMSE value with EBLUP has five times
to be large with only one outlier are included in the data analysis. As for the REBLUP method is relatively more
stable RMSE results.
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