Results 11 to 20 of about 5,491 (290)
Scientific African, 2022 The parameters in the Poisson regression model are usually estimated using the maximum likelihood estimator (MLE). MLE suffers a breakdown when there is either multicollinearity or outliers in the Poisson regression model.
Kingsley Chinedu Arum
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A New Mixed Biased Estimator for Ill‐Conditioning Challenges in Linear Regression Model With Chemometrics Applications [PDF]
Analytical Science AdvancesIn linear regression models, the ordinary least squares (OLS) method is used to estimate the unknown regression coefficients. However, the OLS estimator may provide unreliable estimates in non‐orthogonal models.
Muhammad Amin +3 more
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A bias-reduced estimator for generalized Poisson regression with application to carbon dioxide emission in Canada [PDF]
Scientific ReportsThe generalized Poisson regression model (GPRM) provides a flexible framework for modeling count data, especially those exhibiting over- or underdispersion.
Fatimah M. Alghamdi +6 more
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Transfer Learning for Moderate–Dimensional Ridge-Regularized Robust Linear Regression [PDF]
EntropyThis paper studies transfer learning for ridge-regularized robust linear regression in the moderate–dimensional regime, where the number of predictors is of the same order as the sample size and the regression coefficients are not assumed to be sparse ...
Lingfeng Lyu, Xiao Guo, Zongqi Liu
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Modifying Two-Parameter Ridge Liu Estimator Based on Ridge Estimation
Pakistan Journal of Statistics and Operation Research, 2019 In this paper, we introduce the new biased estimator to deal with the problem of multicollinearity. This estimator is considered a modification of Two-Parameter Ridge-Liu estimator based on ridge estimation. Furthermore, the superiority of the new estimator than Ridge, Liu and Two-Parameter Ridge-Liu estimator were discussed.
Omara, Tarek Mahmoud
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Robust weighted ridge regression based on S – estimator
African Scientific Reports, 2023 Ordinary least squares (OLS) estimator performance is seriously threatened by correlated regressors often called multicollinearity. Multicollinearity is a situation when there is strong relationship between any two exogenous variables.
Taiwo Stephen Fayose +3 more
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Evaluation of Two Stage Modified Ridge Estimator and Its Performance
Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2018 Biasedestimation methods are more desirable than two stage least squares estimationfor simultaneous equations models suffering from the problem ofmulticollinearity.
Selma Toker, Nimet Özbay
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Improving generalized ridge estimator for the gamma regression model. [PDF]
المجلة العراقية للعلوم الاحصائيةIt has been consistently proven that the ridge estimator is an effective shrinking strategy for reducing the effects of multicollinearity. An effective model to use when the response variable is positively skewed is the Gamma Regression Model (GRM ...
AVAN Al-Saffar, Zakaria Y. Algamal
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New ridge parameter estimators for the quasi-Poisson ridge regression model
Scientific ReportsThe quasi-Poisson regression model is used for count data and is preferred over the Poisson regression model in the case of over-dispersed count data.
Aamir Shahzad +3 more
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A stochastic restricted ridge regression estimator
Journal of Multivariate Analysis, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Özkale M.R.
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