References in zbMATH (referenced in 28 articles )

Showing results 1 to 20 of 28.
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  1. Coskun, Burcin; Alpu, O.: Diagnostics of multiple group influential observations for logistic regression models (2019)
  2. Minary, Pauline; Pichon, Frédéric; Mercier, David; Lefevre, Eric; Droit, Benjamin: Evidential joint calibration of binary SVM classifiers (2019)
  3. Schaeben, H.; Kost, S.; Semmler, G.: Popular raster-based methods of prospectivity modeling and their relationships (2019)
  4. Tapia, Alejandra; Leiva, Victor; Diaz, Maria del Pilar; Giampaoli, Viviana: Influence diagnostics in mixed effects logistic regression models (2019)
  5. Zarei, Shaho; Mohammadpour, Adel: Using synthetic data and dimensionality reduction in high-dimensional classification via logistic regression (2019)
  6. Zhang, Chun-Xia; Xu, Shuang; Zhang, Jiang-She: A novel variational Bayesian method for variable selection in logistic regression models (2019)
  7. Zhang, Zhiwang; He, Jing; Gao, Guangxia; Tian, Yingjie: Sparse multi-criteria optimization classifier for credit risk evaluation (2019)
  8. Abdel Aal, Medhat M.; Saad Mowafy, Mamdouh A. Alim; Etman, Nehal: A statistical approach for understanding the plethora of miRNAs and mRNAs interplay (2018)
  9. Aduenko, Alexander A.; Motrenko, Anastasia P.; Strijov, Vadim V.: Object selection in credit scoring using covariance matrix of parameters estimations (2018)
  10. Aragon, Davi C.; Achcar, Jorge A.; Martinez, Edson Z.: Maximum likelihood and Bayesian estimators for the double Poisson distribution (2018)
  11. Bergtold, Jason S.; Pokharel, Krishna P.; Featherstone, Allen M.; Mo, Lijia: On the examination of the reliability of statistical software for estimating regression models with discrete dependent variables (2018)
  12. Heinze, Georg; Wallisch, Christine; Dunkler, Daniela: Variable selection -- a review and recommendations for the practicing statistician (2018)
  13. Özkale, M. Revan; Lemeshow, Stanley; Sturdivant, Rodney: Logistic regression diagnostics in ridge regression (2018)
  14. Tan, Linda S. L.; Nott, David J.: Gaussian variational approximation with sparse precision matrices (2018)
  15. Wang, HaiYing; Zhu, Rong; Ma, Ping: Optimal subsampling for large sample logistic regression (2018)
  16. Yuan, Miao; Tang, Cheng Yong; Hong, Yili; Yang, Jian: Disentangling and assessing uncertainties in multiperiod corporate default risk predictions (2018)
  17. Asar, Yasin; Arashi, Mohammad; Wu, Jibo: Restricted ridge estimator in the logistic regression model (2017)
  18. Bertsimas, Dimitris; King, Angela: Logistic regression: from art to science (2017)
  19. Conversano, Claudio; Dusseldorp, Elise: Modeling threshold interaction effects through the logistic classification trunk (2017)
  20. Miyata, Yoichi: Laplace approximations and Bayesian information criteria in possibly misspecified models (2017)

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