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LassoBacktracking (version 1.1)

Modelling Interactions in High-Dimensional Data with Backtracking

Description

Implementation of the algorithm introduced in Shah, R. D. (2016) . Data with thousands of predictors can be handled. The algorithm performs sequential Lasso fits on design matrices containing increasing sets of candidate interactions. Previous fits are used to greatly speed up subsequent fits, so the algorithm is very efficient.

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Version

Install

install.packages('LassoBacktracking')

Monthly Downloads

205

Version

1.1

License

GPL (>= 2)

Maintainer

Rajen Shah

Last Published

December 8th, 2022

Functions in LassoBacktracking (1.1)

LassoBT

Fit linear models with interactions using the Lasso.
predict.BT

Make predictions from a "BT" object.
cvLassoBT

Cross-validation for LassoBT