tilting-package: Variable Selection via Tilted Correlation Screening Algorithm

In tilting: Variable Selection via Tilted Correlation Screening Algorithm

Description

Implements an algorithm for variable selection in high-dimensional linear regression using the "tilted correlation", a 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:	1.1.1
Date:	2016-12-22
License:	GPL (>= 2)
LazyLoad:	yes

The main function of the package is tilting.

Author(s)

Haeran Cho, Piotr Fryzlewicz

Maintainer: Haeran Cho <[e-mail]>

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

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

tilting documentation built on May 2, 2019, 8:53 a.m.