Selective Inference for the Randomized Lasso

Confidence intervals and p-values for parameters chosen by the (randomized) lasso, valid after selection. Implements the polyhedral approach of Lee, Sun, Sun and Taylor (2016) , the randomized response of Tian and Taylor (2018) and the exact randomized inference of Panigrahi, Fry and Taylor (2024) , with the truncated bivariate normal computations of Liu (2023) . Includes inference for user-specified estimands, screening of inactive variables and problems fitted by 'glmnet'. Computations use a 'C++' backend with matrix-free linear operators for wide designs.