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Communications in Statistics - Simulation and Computation Volume 50, 2021 - Issue 7
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Original Articles

On the relationship between multicollinearity and separation in logistic regression

Guoping Zenga 4522 Oak Shores Dr, Plano, TX, USACorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-3403-5418
ORCID Icon &
Emily Zengb College of Letters & Science, University of California at Berkeley, Berkeley, CA, USA
Pages 1989-1997 | Received 22 Oct 2018, Accepted 26 Feb 2019, Published online: 28 Mar 2019

References

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  • Zeng, G. 2013. Metric divergence measures and information value in credit scoring. Journal of Mathematics 2013:1. Article ID 848271. doi:https://doi.org/10.1155/2013/848271.
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  • Zeng, G. 2017a. A comparison study of computational methods of kolmogorov–smirnov statistic in credit scoring. Communications in Statistics: Simulation and Computation 46 (10):7744–60. doi:https://doi.org/10.1080/03610918.2016.1249883.
  • Zeng, G. 2017b. Invariant properties of logistic regression model in credit scoring under monotonic transformations. Communications in Statistics: Theory and Methods 46 (17):8791–807. doi:https://doi.org/10.1080/03610926.2016.1193200.
  • Zeng, G. 2017c. On the existence of maximum likelihood estimates for weighted logistic regression. Communications in Statistics: Theory and Methods 46 (22):11194–203. doi:https://doi.org/10.1080/03610926.2016.1260743.
  • Zeng, G., and E. Zeng. 2018. On the three-way equivalence of AUC in credit scoring with tied scores. Communications in Statistics: Theory and Methods. doi:https://doi.org/10.1080/03610926.2018.1435814
  • Zeng, G. 2019. On the confusion matrix in credit scoring and its analytical properties. Submitted to Communications in Statistics: Theory and Method. doi:https://doi.org/10.1080/03610926.2019.1568485

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