Modelling Interactions in High-Dimensional Data with Backtracking R package LassoBacktracking version 1.1 Implementation of the algorithm introduced in Shah, R. D. (2016) <https://www.jmlr.org/papers/volume17/13-515/13-515.pdf>. 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. Software Imports: Matrix, parallel, Rcpp LinkingTo: Rcpp Rajen Shah <r.shah@statslab.cam.ac.uk> Comprehensive R Archive Network (CRAN) Rajen Shah [aut, cre] GPL (>= 2) 2022-12-08 application/tgz https://CRAN.R-project.org/package=LassoBacktracking doi:10.32614/CRAN.package.LassoBacktracking