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}
}
  • V. Zuber, K. Strimmer
  • Published 2011
  • Mathematics
  • Statistical Applications in Genetics and Molecular Biology
  • 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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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 38 REFERENCES
    Simultaneous regression shrinkage, variable selection, and supervised clustering of predictors with OSCAR.
    372
    High dimensional variable selection via tilting
    69
    Covariance-regularized regression and classification for high-dimensional problems.
    193
    A Selective Overview of Variable Selection in High Dimensional Feature Space.
    672
    Gene ranking and biomarker discovery under correlation
    89
    Least angle regression
    7746
    Regression Shrinkage and Selection via the Lasso
    28779
    Sure independence screening for ultrahigh dimensional feature space
    1622
    RANDOM LASSO.
    83