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dc.contributor.authorM. I. ALHEETY, Kristofer Månsson-
dc.contributor.authorB. M. Golam Kibria-
dc.date.accessioned2022-10-26T18:10:18Z-
dc.date.available2022-10-26T18:10:18Z-
dc.date.issued2020-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/6991-
dc.description.abstractIn the logistic regression model, the variance of the maximum likelihood estimator is inflated and unstable when the multicollinearity exists in the data. There are several methods available in literature to overcome this problem. We propose a new stochastic restricted biased estimator. We study the statistical properties of the proposed estimator and compare its performance with some existing estimators in the sense of scalar mean squared criterion. An example and a simulation study are provided to illustrate the performance of the proposed estimator.en_US
dc.language.isoenen_US
dc.publisherJournal of Applied Statisticsen_US
dc.subjectLogistic regression; maximum likelihooden_US
dc.subjectestimator; mean squared error matrix; ridge regression;en_US
dc.titleA new kind of stochastic restricted biased estimator for logistic regression modelen_US
dc.typeArticleen_US
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