# High-Dimensional Regression and Variable Selection Using CAR Scores

@article{Zuber2011HighDimensionalRA, title={High-Dimensional Regression and Variable Selection Using CAR Scores}, author={V. Zuber and K. Strimmer}, journal={Statistical Applications in Genetics and Molecular Biology}, year={2011}, volume={10} }

Variable selection is a difficult problem that is particularly challenging in the analysis of high-dimensional genomic data. Here, we introduce the CAR score, a novel and highly effective criterion for variable ranking in linear regression based on Mahalanobis-decorrelation of the explanatory variables. The CAR score provides a canonical ordering that encourages grouping of correlated predictors and down-weights antagonistic variables. It decomposes the proportion of variance explained and it… CONTINUE READING

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