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Robust logistic regression in the presence of high leverage points | ||
| Journal of Al-Qadisiyah for Computer Science and Mathematics | ||
| Article 1, Volume 11, Issue 3, 2019, Pages 1-11 PDF (0 K) | ||
| Author | ||
| Mohammed A. Mohammed | ||
| Abstract | ||
| In this article we conceder the logistic regression model with high leverage points. For the logistic regression model with a binary response, we suggested a new robust approach called robust logistic regression (RLR) based on the robust mahalanobis distance (RMD) which depends on the minimum volume ellipsoid (MVE) estimators. The RMD is computed by using the algorithm of stochastic gradient descent (SGD). In order to assist the new suggested approach we compare it with some existing method such as maximum likelihood estimator and robust M-estimator in logistic regression model. The simulation study points that the RLR has supreme performances throw some measurement comparison. | ||
| Keywords | ||
| Logistic regression model; MVE; RMD; SGD and HLPs | ||
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