Efficiency of the Principal Component Liu-Type Estimator in Logistic Regression
Revstat Statistical Journal, 2020 In this paper we propose a principal component Liu-type logistic estimator by combining the principal component logistic regression estimator and Liu-type logistic estimator to overcome the multicollinearity problem. The superiority of the new estimator
Jibo Wu , Yasin Asar
doaj +1 more source
Shifted Liu-Type Estimator in The Linear Regression
, 2022 The methods to solve the problem of multicollinearity have an important issue in the linear regression. The Liu-type estimator is one of these methods used to reduce its effect. This estimator is an estimator with two parameters denoted and . Kurnaz and
Erdugan, Funda
core +1 more source
A new class of Poisson Ridge-type estimator
Scientific Reports, 2023 The Poisson Regression Model (PRM) is one of the benchmark models when analyzing the count data. The Maximum Likelihood Estimator (MLE) is used to estimate the model parameters in PRMs. However, the MLE may suffer from various drawbacks that arise due to
Esra Ertan, Kadri Ulaş Akay
doaj +1 more source
K-L Estimator: Dealing with Multicollinearity in the Logistic Regression Model
Mathematics, 2023 Multicollinearity negatively affects the efficiency of the maximum likelihood estimator (MLE) in both the linear and generalized linear models. The Kibria and Lukman estimator (KLE) was developed as an alternative to the MLE to handle multicollinearity ...
Adewale F. Lukman +5 more
doaj +1 more source
A High-Dimensional Counterpart for the Ridge Estimator in Multicollinear Situations
Mathematics, 2021 The ridge regression estimator is a commonly used procedure to deal with multicollinear data. This paper proposes an estimation procedure for high-dimensional multicollinear data that can be alternatively used.
Mohammad Arashi +3 more
doaj +1 more source
Liu-Type logistic estimator under Stochastic Linear Restrictions
Ceylon Journal of Science, 2018 To conquer the multicollinearity problem in logistic regression, many alternative estimators have been proposed in the literature when some linear restrictions on the parameter space are available in addition to the sample model.
Nagarajah Varathan +1 more
doaj +1 more source
Some one and two parameter estimators for the multicollinear gaussian linear regression model: simulations and applications [PDF]
Surveys in Mathematics and its Applications, 2023 The ordinary least square estimator is inefficient when there exists multicollinearity among regressors in linear regression model. There are many methods available in literature to solve the multicollinearity problem. In this study, we consider some one
Md Ariful Hoque , B. M. Golam Kibria
doaj
A new almost unbiased estimator in stochastic linear restriction model [PDF]
المجلة العراقية للعلوم الاحصائية, 2011 In this paper, a new almost unbiased estimator is proposed under stochastic linear restrictions model as alternative to mixed estimator. The performance of the proposed estimator compared to mixed estimator is examined using the matrix mean squared ...
Mustafa Ismaeel Naif
doaj +1 more source
Assessment Restricted Liu Estimator to treating Multicollinearity Problem [PDF]
المجلة العراقية للعلوم الاحصائية, 2006 In this research, we compared restricted least squares with restricted Liu estimator . by using (MSE) criterion in the existence of multicollinearity. We found that restricted Liu estimator is the best in comparison.
doaj +1 more source
A New Tobit Ridge-Type Estimator of the Censored Regression Model With Multicollinearity Problem
Frontiers in Applied Mathematics and Statistics, 2022 In the censored regression model, the Tobit maximum likelihood estimator is unstable and inefficient in the occurrence of the multicollinearity problem.
Issam Dawoud +3 more
doaj +1 more source