Robust variable selection in the logistic regression model

Yıl 2021, Cilt: 50 Sayı: 5, 1572 - 1582, 15.10.2021

Yunlu Jıang Jianto Zhang Yingqiang Huang Hang Zou Meilan Huang Fanhong Chen

https://doi.org/10.15672/hujms.810383

Öz

In this paper, we proposed an adaptive robust variable selection procedure for the logistic regression model. The proposed method is robust to outliers and considers the goodness-of-fit of the regression model. Furthermore, we apply an MM algorithm to solve the proposed optimization problem. Monte Carlo studies are evaluated the finite-sample performance of the proposed method. The results show that when there are outliers in the dataset or the distribution of covariate variable deviates from the normal distribution, the finite-sample performance of the proposed method is better than that of other existing methods.
Finally, the proposed methodology is applied to the data analysis of Parkinson's disease.

Anahtar Kelimeler

Logistic regression, Variable selection, Robustness, MM algorithm

Kaynakça

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