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

被引:2
作者
Alheety, M. I. [1 ]
Mansson, Kristofer [2 ]
Golam Kibria, B. M. [3 ]
机构
[1] Univ Anbar, Coll Educ Pure Sci, Dept Math, Ramadi, Iraq
[2] Jonkoping Univ, Dept Econ Finance & Stat, Jonkoping, Sweden
[3] Florida Int Univ, Dept Math & Stat, Miami, FL 33199 USA
关键词
Logistic regression; maximum likelihood estimator; mean squared error matrix; ridge regression; simulation study; stochastic restricted estimator; RIDGE-REGRESSION; LIU ESTIMATOR; PARAMETERS;
D O I
10.1080/02664763.2020.1769576
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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.
引用
收藏
页码:1559 / 1578
页数:20
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