A test of harmful multicollinearity: A generalized ridge regression approach
Sign Up to like & getrecommendations! Published in 2020 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2020.1754855
Abstract: Abstract This paper introduces a new test of harmful multicollinearity based on the ratio of the levels of significance of ordinary least squares and generalized ridge regression estimates of the coefficients. Harmful multicollinearity is the… read more here.
Keywords: harmful multicollinearity; multicollinearity; test; test harmful ... See more keywords
Quantile-Based Estimation of Liu Parameter in the Linear Regression Model: Applications to Portland Cement and US Crime Data
Sign Up to like & getrecommendations! Published in 2021 at "Mathematical Problems in Engineering"
DOI: 10.1155/2021/1772328
Abstract: In multiple linear regression models, the multicollinearity problem mostly occurs when the explanatory variables are correlated among each other. It is well known that when the multicollinearity exists, the variance of the ordinary least square… read more here.
Keywords: multicollinearity; regression; linear regression; portland cement ... See more keywords
Modified Liu estimators in the linear regression model: An application to Tobacco data
Sign Up to like & getrecommendations! Published in 2021 at "PLoS ONE"
DOI: 10.1371/journal.pone.0259991
Abstract: Background The problem of multicollinearity in multiple linear regression models arises when the predictor variables are correlated among each other. The variance of the ordinary least squared estimator become unstable in such situation. In order… read more here.
Keywords: multicollinearity; regression; linear regression; shrinkage parameter ... See more keywords
Some Modified Ridge Estimators for Handling the Multicollinearity Problem
Sign Up to like & getrecommendations! Published in 2023 at "Mathematics"
DOI: 10.3390/math11112522
Abstract: Regression analysis is a statistical process that utilizes two or more predictor variables to predict a response variable. When the predictors included in the regression model are strongly correlated with each other, the problem of… read more here.
Keywords: problem; multicollinearity; estimators handling; ridge estimators ... See more keywords
Ridge Fuzzy Regression Modelling for Solving Multicollinearity
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DOI: 10.3390/math8091572
Abstract: This paper proposes an α-level estimation algorithm for ridge fuzzy regression modeling, addressing the multicollinearity phenomenon in the fuzzy linear regression setting. By incorporating α-levels in the estimation procedure, we are able to construct a… read more here.
Keywords: regression; multicollinearity; regression modelling; fuzzy regression ... See more keywords
On the Estimation of the CO2 Emission, Economic Growth and Energy Consumption Nexus Using Dynamic OLS in the Presence of Multicollinearity
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DOI: 10.3390/su10051315
Abstract: This paper introduces shrinkage estimators (Ridge DOLS) for the dynamic ordinary least squares (DOLS) cointegration estimator, which extends the model for use in the presence of multicollinearity between the explanatory variables in the cointegration vector.… read more here.
Keywords: energy consumption; multicollinearity; method; presence multicollinearity ... See more keywords