15 articles for “Multicollinearity”

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Research ArticleOpen accessIn the keywordsA Comparative Study of the Performances of the OLS and some GLS Estimators when Stochastic Regressors are both Collinear and Correlated with Error TermsKayode AyindeThe Classical Linear Regression Model assumes that regressors are non – stochastic, independent and uncorrelated with the error terms. These assumptions are not always tenable especially where regressors are not often assumed fixed in repeated sampling. In this paper, with stochastic regressors, the performances of the Ordinary Least Square (OLS) and some Generalized Least Square (GLS) estimators are investigated and … …Journal of Mathematics and Statistics, Vol. 3, Issue 4 · 31 Dec 2007 · 7,343 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsCA-LIME: A Collinearity-Aware LIME Framework for Reliable and Interpretable Explanations in Healthcare AIIdris Khan, Sachin BhoiteIn clinical tabular models, correlated biomarkers can make local explanations unstable even when predictive performance appears acceptable. This paper presents CA-LIME, a collinearity-aware extension of LIME built to address that failure mode directly. Five variations of CA-LIME Vanilla reference, VIF, PCA back projection, Ridge, and ElasticNet allow us to investigate how various correlation-control strategies alter explanation behavior. ILPD, Kaggle liver, … …Journal of Computer Science, Vol. 22, Issue 7 · 28 Jul 2026 · 806 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsComparison of Collinearity Indices for Linear Models in Agricultural TrialsDanny Villegas Rivas, José M. Palacios Sánchez, Cristina A. Alzamora Rivero et al.The deleterious consequences of collinearity in linear regression on the precision of estimators of regression coefficients and the interpretability of the fitted model are widely recognized. In this study, we compare several methodologies for assessing collinearity in linear models and explore the effect of outliers on collinearity. The robustness of collinearity measures (individual and overall) is validated through two detailed … …OnLine Journal of Biological Sciences, Vol. 24, Issue 2 · 28 Dec 2023 · 6,491 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsPERFORMANCE OF RIDGE REGRESSION ESTIMATOR METHODS ON SMALL SAMPLE SIZE BY VARYING CORRELATION COEFFICIENTS: A SIMULATION STUDYAnwar Fitrianto, Lee Ceng YikWhen independent variables have high linear correlation in a multiple linear regression model, we can have wrong analysis. It happens if we do the multiple linear regression analysis based on common Ordinary Least Squares (OLS) method. In this situation, we are suggested to use ridge regression estimator. We conduct some simulation study to compare the performance of ridge regression estimator … …Journal of Mathematics and Statistics, Vol. 10, Issue 1 · 3 Jan 2014 · 8,540 accessesView PDF Cite

Research ArticleOpen accessIn the abstractTwo-Stage Estimation in Inverse Problems using Combined Wavelet Thresholding and Penalized Maximum LikelihoodRobert G Aykroyd, Hassan AljohaniInverse problems occur in a wide range of practical scientific investigations where the variables of interest are only observed indirectly, such as magnetic and seismic imaging in geophysics, electrical tomography in industrial process monitoring, or PET scanning in medicine. Linear inverse problems can be thought of as highly multivariate regression problems with strong multicollinearity where the aim is to interpret … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 29 Sep 2017 · 7,925 accessesView PDF Cite