Package: hdme
Type: Package
Title: High-Dimensional Regression with Measurement Error
Version: 0.5.1
Encoding: UTF-8
Authors@R: c(person("Oystein", "Sorensen", 
                    email = "oystein.sorensen.1985@gmail.com", 
                    role = c("aut", "cre"),
                    comment = c(ORCID = "0000-0003-0724-3542")))
Maintainer: Oystein Sorensen <oystein.sorensen.1985@gmail.com>
Description: 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>).
License: GPL-3
RoxygenNote: 7.2.0
Imports: glmnet (>= 3.0.0), ggplot2 (>= 2.2.1), Rdpack, Rcpp (>=
        0.12.15), Rglpk (>= 0.6-1), stats
URL: https://github.com/osorensen/hdme
RdMacros: Rdpack
Suggests: knitr, rmarkdown, testthat, dplyr, tidyr, covr
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2023-02-28 09:07:42 UTC; oyss
Author: Oystein Sorensen [aut, cre] (<https://orcid.org/0000-0003-0724-3542>)
Repository: CRAN
Date/Publication: 2023-02-28 09:22:30 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-17 17:33:50 UTC; windows
Archs: i386, x64
