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
doaj +2 more sources
Ridge regression estimator: combining unbiased and ordinary ridge regression methods of estimation [PDF]
Surveys in Mathematics and its Applications, 2009 Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR).
Sharad Damodar Gore, Feras Sh. M. Batah
doaj +2 more sources
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
doaj +2 more sources
New robust estimator for handling outliers and multicollinearity in gamma regression model with application to breast cancer data [PDF]
Scientific ReportsThe gamma regression model (GRM) is commonly used to analyze continuous data that are positively skewed. However, the GRM is sensitive to multicollinearity and outliers. These two problems often occur in regression analysis.
Arwa M. Alshangiti +7 more
doaj +2 more sources
Development of the generalized ridge estimator for the Poisson-Inverse Gaussian regression model with multicollinearity [PDF]
Scientific ReportsThe Poisson-Inverse Gaussian regression model is a widely used method for analyzing count data, particularly in over-dispersion. However, the reliability of parameter estimates obtained through maximum likelihood estimation in this model can be ...
Fatimah A. Almulhim +5 more
doaj +2 more sources
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
doaj +3 more sources
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 +3 more sources
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
doaj +2 more sources
Estimation methods of logistic regression in context of multicollinearity (Comparative study) [PDF]
Maǧallaẗ Al-Buḥūṯ Al-Tiǧāriyyaẗ, 2023 The binary logistic regression (BLR) model is used as an alternative to the commonly used linear regression model when the response variable is binary.
Hassan Mohamed Ali +2 more
doaj +1 more source
Another Look at Partitioned Ridge Regression Estimators [PDF]
The Egyptian Statistical Journal, 1992 Several biased estimators have been proposed as alternatives to the Least squares estimator when multicollinearity is present in the multiple linear regression model.
Linda Abskharoon, Mahmoud Mahmoud
doaj +1 more source