In this study, we investigate whether the Tukey M robust regression method provides a solution for data sets suffering from multicollinearity problem. It is observed that high values of variance inflation factors (VIF) which sign multiple linear link among explanatory variables, cannot be controlled by methods work through residual values. The reason fact and VIF result do not produce extreme r...

Recent reports of an inverse association between dietary calcium intake and hypertension stimulated this analysis of the relationship of blood pressure to more than 20 dietary factors among a group of 8000 Japanese men in Hawaii. Reported intakes of potassium, calcium, protein, and milk were all inversely associated with blood pressure levels when examined one at a time while controlling for ot...

The effects of multicollinearity in all possible model selection of fixed effects including quadratic and cross products in the presence of random and repeated measures effects are presented here. The user-friendly SAS macro application ALLMIXED2 complements the model selection option currently available in the SAS macro applications ‘REGDIAG’ and ‘LOGISTIC’ for multiple linear and logistic reg...

The evidence presented by Haas and Stack (1983) suggests that a parabolic relationship exists between a nation's level of industrialization and the strike activity among its labor force. Their model is tested using data from a different time period. Criticisms of the original model, including problems of heteroskedasticity, autocorrelation and multicollinearity, are addressed here. The findings...

A model is constructed, using Eurobarometer data, of the propensity of individuals to favour European integration. A key role is played by economic considerations: countries in which income per capita is relatively low contain individuals that are more positive in their attitudes to Europe; growth is associated with more positive attitudes; economic fluctuations, above a threshold, are associat...

Data collected from Kelly Blue Book for several hundred 2005 used General Motors (GM) cars allows students to develop a multivariate regression model to determine car values based on a variety of characteristics such as mileage, make, model, engine size, interior style, and cruise control. Students learn to look at residual plots to check for heteroskedasticity, normality, autocorrelation, and ...

§ The insights gained from this study could be useful in selecting machine-learning methods for automated pre-processing of thousands of correlated variables in biomedical data mining. Conclusions Comparison of machine learning techniques for handling multicollinearity in big data analytics and high-performance data mining Gerard G. Dumancas1* and Ghalib Bello2 *1Oklahoma Baptist University, S...

Fuzzy regression models has been traditionally considered as a problem of linear programming. We introduce new models founded on quadratic programming with the aim of overcoming the limitations of linear programming, and that allow to define a great amplitude of wide variety. We verify the existence of multicollinearity in fuzzy regression and we propose a model based on Ridge regression in ord...