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 Arum
exaly +3 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
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
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
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
Modified Ridge Logistic Estimator Based on Singular Value Decomposition [PDF]
The Egyptian Statistical Journal, 2023 This paper aims to introduce a modification of the ridge estimator based on the singular value decomposition (SVD) technique of the design matrix (X ) to combat multicollinearity in the binary logistic model.
Monira Hussein, Mostafa Abd el-Rahman
doaj +1 more source
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
Modified Jackknifed Ridge Estimator in Bell Regression Model: Theory, Simulation and Applications
Iraqi Journal for Computer Science and Mathematics, 2023 Regression models explore the relationship between the response variable and one or more explanatory variables. It becomes practically challenging in real-life applications to model this relationship when the explanatory variables are linearly dependent.
Zakariya Algamal +3 more
doaj +1 more source
Ridge regression and its applications in genetic studies.
PLoS ONE, 2021 With the advancement of technology, analysis of large-scale data of gene expression is feasible and has become very popular in the era of machine learning. This paper develops an improved ridge approach for the genome regression modeling.
M Arashi +3 more
doaj +1 more source
Modified jackknife ridge estimator for the Conway-Maxwell-Poisson model
Scientific African, 2023 Recently, research papers have shown a strong interest in modeling count data. The over-dispersion or under-dispersion are frequently seen in the count data.
Zakariya Yahya Algamal +3 more
doaj +1 more source