Variable Selection via Tilted Correlation Screening Algorithm

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Description

Implements an algorithm for variable selection in high-dimensional linear regression using the "tilted correlation", a new way of measuring the contribution of each variable to the response which takes into account high correlations among the variables in a data-driven way.

Details

Package: tilting
Type: Package
Version: 1.1
Date: 2016-06-20
License: GPL (>= 2)
LazyLoad: yes

The main function of the package is tilting.

Author(s)

Haeran Cho Maintainer: Haeran Cho <haeran.cho@bristol.ac.ukk>

References

H. Cho and P. Fryzlewicz (2012) High-dimensional variable selection via tilting, Journal of the Royal Statistical Society Series B, 74: 593-622.

Examples

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X <- matrix(rnorm(100*100), 100, 100) # 100-by-100 design matrix
y <- apply(X[,1:5], 1, sum)+rnorm(100) # first five variables are significant

tilt <- tilting(X, y, op=2)
tilt$active.hat # returns the finally selected variables