Results 21 to 30 of about 1,043 (255)
Modified Unbiased Optimal Estimator For Linear Regression Model [PDF]
مجلة جامعة الانبار للعلوم الصرفة, 2023 In this paper, we propose a novel form of Generalized Unbiased Optimal Estimator where the explanatory variables are multicollinear. The proposed estimator's bias, variance, and mean square error matrix (MSE) are calculated.
Hussein AL-jumaili, Mustafa Alheety
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BAYESIAN-RIDGE ESTIMATOR FOR LINEAR REGRESSION MODEL
, 2023 Multicollinearity is a problem associated with inter-dependence of explanatory variables in linear regression model. The inefficiency of the Ordinary Least Square (OLS) Estimator lead to development of various other methods which include the Ridge ...
Idowu Usman
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Ridge Estimation for Multinomial Logit Models with Symmetric Side Constraints [PDF]
, 2009 In multinomial logit models, the identifiability of parameter estimates is typically obtained by side constraints that specify one of the response categories as reference category.
Tutz, Gerhard, Zahid, Faisal Maqbool
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Combining modified ridge-type and principal component regression estimators
Scientific African, 2020 The performance of ordinary least squares estimator (OLSE) when there is multicollinearity (MC) in a linear regression model becomes inefficient. The principal components regression and the modified ridge-type estimator have been proposed at a different ...
Adewale F. Lukman +3 more
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F1000Research, 2021 Background: In the linear regression model, the ordinary least square (OLS) estimator performance drops when multicollinearity is present. According to the Gauss-Markov theorem, the estimator remains unbiased when there is multicollinearity, but the ...
BENEDICTA Aladeitan +4 more
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An unbiased estimator with prior information
Arab Journal of Basic and Applied Sciences, 2020 The ordinary least square (OLS) estimator suffers a breakdown in the presence of multicollinearity. The estimator is still unbiased but possesses a significant variance.
Adewale F. Lukman +3 more
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Generalized Kibria-Lukman Estimator: Method, Simulation, and Application
Frontiers in Applied Mathematics and Statistics, 2022 In the linear regression model, the multicollinearity effects on the ordinary least squares (OLS) estimator performance make it inefficient. To solve this, several estimators are given. The Kibria-Lukman (KL) estimator is a recent estimator that has been
Issam Dawoud +2 more
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Comparison of Some Estimators under the Pitman’s Closeness Criterion in Linear Regression Model
Journal of Applied Mathematics, 2014 Batah et al. (2009) combined the unbiased ridge estimator and principal components regression estimator and introduced the modified r-k class estimator.
Jibo Wu
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The VIF and MSE in Raise Regression
Mathematics, 2020 The raise regression has been proposed as an alternative to ordinary least squares estimation when a model presents collinearity. In order to analyze whether the problem has been mitigated, it is necessary to develop measures to detect collinearity after
Román Salmerón Gómez +3 more
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Modified Robust Ridge M-Estimators in Two-Parameter Ridge Regression Model [PDF]
, 2021 The methods of two-parameter ridge and ordinary ridge regression are very sensitive to the presence of the joint problem of multicollinearity and outliers in the y-direction. To overcome this problem, modified robust ridge M-estimators are proposed.
Ayed, Hamdi +5 more
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