A ridge logistic estimator
Robert L. Schaefer, Larry D. Roi, Robert A. Wolfe
Abstract
Robert L. Schaefer, Larry D. Roi, Robert A. Wolfe
Abstract
It is found that multicollinearity among the independent variables in logistic regression inflates the variances of the maximum likelihood estimator. A Ridge type estimator is proposed that will have smaller total mean squared error than the maximum likelihood estimator under certain conditions. Empirical study results are presented that evaluate this estimator for different sample sizes and degrees of multicollinearity.
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It is found that multicollinearity among the independent variables in logistic regression inflates the variances of the maximum likelihood estimator. A Ridge type estimator is proposed that will have smaller total mean squared error than the maximum likelihood estimator under certain conditions. Empirical study results are presented that evaluate this estimator for different sample sizes and degrees of multicollinearity.
Key concepts: Ridge, Estimator, Geology, Computer science, Statistics, Environmental science, Mathematics, Paleontology