A new kind of stochastic restricted biased estimator for logistic regression model
© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
| Publié dans: | Journal of applied statistics. - 1991. - 48(2021), 9 vom: 12., Seite 1559-1578 |
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| Auteur principal: | |
| Autres auteurs: | , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2021
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| Accès à la collection: | Journal of applied statistics |
| Sujets: | Journal Article Logistic regression Primary 62J05 Secondary 62J07 maximum likelihood estimator mean squared error matrix ridge regression simulation study stochastic restricted estimator |
| Résumé: | © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. In 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 |
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| Description: | Date Revised 16.06.2022 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
| ISSN: | 0266-4763 |
| DOI: | 10.1080/02664763.2020.1769576 |