PERBANDINGAN REGRESI ROBUST PENDUGA MM DENGAN METODE RANDOM SAMPLE CONSENSUS DALAM MENANGANI PENCILAN
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https://doi.org/10.24843/MTK.2014.v03.i02.p065
Abstrak
The presence of outliers in observation can result in biased in parameter estimation using ordinary least square (OLS). Robust regression MM-estimator is one of the estimations methods that able to obtain a robust estimator against outliers. Random sample consensus (ransac) is another method that can be used to construct a model for observations data and also estimating a robust estimator against outliers. Based on the study, ransac obtained model with less biased estimator than robust regression MM-estimator.
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Diterbitkan
2014-05-31
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IRFAGUTAMI, NI PUTU NIA; SRINADI, I GUSTI AYU MADE; SUMARJAYA, I WAYAN.
PERBANDINGAN REGRESI ROBUST PENDUGA MM DENGAN METODE RANDOM SAMPLE CONSENSUS DALAM MENANGANI PENCILAN.
E-Jurnal Matematika, [S.l.], v. 3, n. 2, p. 45 - 52, may 2014.
ISSN 2303-1751. Tersedia pada: <http://103.29.196.112/index.php/mtk/article/view/9605>. Tanggal Akses: 04 mar. 2026
doi: https://doi.org/10.24843/MTK.2014.v03.i02.p065.
Terbitan
Bagian
Articles
Kata Kunci
Outlier; Robust Regression; MM-estimate; ransac
This work is licensed under a Creative Commons Attribution 4.0 International License.
