https://jonathan-taylor-stanford.r-universe.devRecent package updates in jonathan-taylor-stanfordR-universehttps://github.com/jonathan-taylor-stanford.pnghttps://jonathan-taylor-stanford.r-universe.devTue, 20 Oct 2026 18:00:02 GMTjtaylo@stanford.edu (Jonathan Taylor)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) <doi:10.1214/15-AOS1371>, the randomized response of Tian and Taylor (2018) <doi:10.1214/17-AOS1564> and the exact randomized inference of Panigrahi, Fry and Taylor (2024) <doi:10.1093/biomet/asae019>, with the truncated bivariate normal computations of Liu (2023) <doi:10.48550/arXiv.2308.10346>. 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.https://github.com/r-universe/jonathan-taylor-stanford/actions/runs/39935400653Tue, 20 Oct 2026 18:00:02 GMTlassoinf0.1.0successhttps://jonathan-taylor-stanford.r-universe.devhttps://github.com/cran/lassoinfglmnet_logistic.Rmdglmnet_logistic.htmlInference after a glmnet fit: carving for logistic regression2026-10-20 18:00:022026-10-20 18:00:02no_randomization.Rmdno_randomization.htmlInference after a glmnet fit without randomization2026-10-20 18:00:022026-10-20 18:00:02gaussian_lasso.Rmdgaussian_lasso.htmlRandomized LASSO for a Gaussian linear model2026-10-20 18:00:022026-10-20 18:00:02screening_inactive.Rmdscreening_inactive.htmlScreening inactive variables2026-10-20 18:00:022026-10-20 18:00:02surrogate_screening.Rmdsurrogate_screening.htmlSurrogate screening: swapping selected and screened variables2026-10-20 18:00:022026-10-20 18:00:02