Results 11 to 20 of about 16,607 (260)

On Liu estimators for the logit regression model [PDF]

open access: yesEconomic Modelling, 2012
This paper introduces a shrinkage estimator for the logit model which is a generalization of the estimator proposed by Liu (1993) for the linear regression. This new estimation method is suggested since the mean squared error (MSE) of the commonly used maximum likelihood (ML) method becomes inflated when the explanatory variables of the regression ...
Månsson, Kristofer   +2 more
openaire   +1 more source

Liu-type shrinkage estimations in linear models

open access: yesStatistics, 2022
In this study, we present the preliminary test, Stein-type and positive part Liu estimators in the linear models when the parameter vector $\boldsymbolβ$ is partitioned into two parts, namely, the main effects $\boldsymbolβ_1$ and the nuisance effects $\boldsymbolβ_2$ such that $\boldsymbolβ=\left(\boldsymbolβ_1, \boldsymbolβ_2 \right)$.
Bahadır Yüzbaşı   +2 more
openaire   +2 more sources

A new biased regression estimator: Theory, simulation and application

open access: yesScientific African, 2022
The linear regression model explores the relationship between a response variable and one or more independent variables. The ordinary least squared estimator is usually adopted to estimate the parameters of the model when the independent variables are ...
Issam Dawoud   +2 more
doaj   +1 more source

A new Liu-type estimator

open access: yesStatistical Papers, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kurnaz, Fatma Sevinc, Akay, Kadri Ulas
openaire   +5 more sources

Modified Kibria-Lukman (MKL) estimator for the Poisson Regression Model: application and simulation [version 2; peer review: 2 approved, 1 approved with reservations]

open access: yesF1000Research, 2021
Background: Multicollinearity greatly affects the Maximum Likelihood Estimator (MLE) efficiency in both the linear regression model and the generalized linear model. Alternative estimators to the MLE include the ridge estimator, the Liu estimator and the
Olukayode Adebimpe   +4 more
doaj   +1 more source

Efficiency of the Principal Component Liu-Type Estimator in Logistic Regression

open access: yesRevstat 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

On the Performance of Principal Component Liu-Type Estimator under the Mean Square Error Criterion

open access: yesJournal of Applied Mathematics, 2013
Wu (2013) proposed an estimator, principal component Liu-type estimator, to overcome multicollinearity. This estimator is a general estimator which includes ordinary least squares estimator, principal component regression estimator, ridge estimator, Liu ...
Jibo Wu
doaj   +1 more source

A new class of Poisson Ridge-type estimator

open access: yesScientific 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

open access: yesMathematics, 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

open access: yesMathematics, 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

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