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A new kind of stochastic restricted biased estimator for logistic regression model

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...

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Detalles Bibliográficos
Autores principales: Alheety, M. I., Månsson, Kristofer, Golam Kibria, B. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9042162/
https://www.ncbi.nlm.nih.gov/pubmed/35706568
http://dx.doi.org/10.1080/02664763.2020.1769576
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author Alheety, M. I.
Månsson, Kristofer
Golam Kibria, B. M.
author_facet Alheety, M. I.
Månsson, Kristofer
Golam Kibria, B. M.
author_sort Alheety, M. I.
collection PubMed
description 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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spelling pubmed-90421622022-06-14 A new kind of stochastic restricted biased estimator for logistic regression model Alheety, M. I. Månsson, Kristofer Golam Kibria, B. M. J Appl Stat Articles 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. Taylor & Francis 2020-05-30 /pmc/articles/PMC9042162/ /pubmed/35706568 http://dx.doi.org/10.1080/02664763.2020.1769576 Text en © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
spellingShingle Articles
Alheety, M. I.
Månsson, Kristofer
Golam Kibria, B. M.
A new kind of stochastic restricted biased estimator for logistic regression model
title A new kind of stochastic restricted biased estimator for logistic regression model
title_full A new kind of stochastic restricted biased estimator for logistic regression model
title_fullStr A new kind of stochastic restricted biased estimator for logistic regression model
title_full_unstemmed A new kind of stochastic restricted biased estimator for logistic regression model
title_short A new kind of stochastic restricted biased estimator for logistic regression model
title_sort new kind of stochastic restricted biased estimator for logistic regression model
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9042162/
https://www.ncbi.nlm.nih.gov/pubmed/35706568
http://dx.doi.org/10.1080/02664763.2020.1769576
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