PERBANDINGAN REGRESI ROBUST PENDUGA MM DENGAN METODE RANDOM SAMPLE CONSENSUS DALAM MENANGANI PENCILAN
Abstract
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.
Downloads
Download data is not yet available.
Published
2014-05-31
How to Cite
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. Available at: <https://ojs.unud.ac.id/index.php/mtk/article/view/9605>. Date accessed: 20 apr. 2024.
doi: https://doi.org/10.24843/MTK.2014.v03.i02.p065.
Issue
Section
Articles
Keywords
Outlier; Robust Regression; MM-estimate; ransac
This work is licensed under a Creative Commons Attribution 4.0 International License.
