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    Kebutuhan Rumah Sederhana di Kabupaten Jember dengan Robust Small Area Estimation (Simple House Needs in Jember with Robust Small Area Estimation)

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    F. MIPA_Jurnal_Frida M_Simple House Needs.pdf (833.1Kb)
    Date
    2017-09-26
    Author
    Murtinasari, Frida
    Hadi, Alfian Futuhul
    Anggraeni, Dian
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    Abstract
    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 MEstimation. 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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    http://repository.unej.ac.id/handle/123456789/81861
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    Indonesia DSpace Group :

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