tilting: Variable Selection via Tilted Correlation Screening Algorithm

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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.

Author
Haeran Cho
Date of publication
2016-06-23 00:37:15
Maintainer
Haeran Cho <mahrc@bristol.ac.uk>
License
GPL (>= 2)
Version
1.1

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Man pages

col.norm
Compute the L2 norm of each column
get.thr
Select a threshold for sample correlation matrix
lse.beta
Compute the least squares estimate on a given index set
projection
Compute the projection matrix onto a given set of variables
select.model
Select the final model
thresh
Hard-threshold a matrix
tilting
Variable selection via Tilted Correlation Screening algorithm
tilting-package
Variable Selection via Tilted Correlation Screening Algorithm

Files in this package

tilting
tilting/NAMESPACE
tilting/R
tilting/R/package.R
tilting/MD5
tilting/DESCRIPTION
tilting/man
tilting/man/lse.beta.Rd
tilting/man/select.model.Rd
tilting/man/thresh.Rd
tilting/man/projection.Rd
tilting/man/col.norm.Rd
tilting/man/tilting-package.Rd
tilting/man/get.thr.Rd
tilting/man/tilting.Rd