High-Dimensional Regression with Measurement Error R package hdme version 0.6.0 Penalized regression for generalized linear models for measurement error problems (aka. errors-in-variables). The package contains a version of the lasso (L1-penalization) which corrects for measurement error (Sorensen et al. (2015) <doi:10.5705/ss.2013.180>). It also contains an implementation of the Generalized Matrix Uncertainty Selector, which is a version the (Generalized) Dantzig Selector for the case of measurement error (Sorensen et al. (2018) <doi:10.1080/10618600.2018.1425626>). Software Imports: glmnet (>= 3.0.0), ggplot2 (>= 2.2.1), Rdpack, Rcpp (>= 0.12.15), Rglpk (>= 0.6-1), rlang (>= 1.0), stats LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, rmarkdown, testthat, dplyr, tidyr, covr Oystein Sorensen <oystein.sorensen.1985@gmail.com> Comprehensive R Archive Network (CRAN) Oystein Sorensen [aut, cre] (ORCID: <https://orcid.org/0000-0003-0724-3542>) GPL-3 2023-05-16 application/tgz https://CRAN.R-project.org/package=hdme doi:10.32614/CRAN.package.hdme