CRAN/E | hdme

hdme

High-Dimensional Regression with Measurement Error

Installation

About

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).

Citation hdme citation info
github.com/osorensen/hdme

Key Metrics

Version 0.6.0
Published 2023-05-16 352 days ago
Needs compilation? yes
License GPL-3
CRAN checks hdme results

Downloads

Yesterday 8 0%
Last 7 days 74 -14%
Last 30 days 289 -6%
Last 90 days 877 -20%
Last 365 days 3.964 -14%

Maintainer

Maintainer

Oystein Sorensen

oystein.sorensen.1985@gmail.com

Authors

Oystein Sorensen

aut / cre

Material

README
NEWS
Reference manual
Package source

Vignettes

The hdme package: regression methods for high-dimensional data with measurement error

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

hdme archive

Imports

glmnet ≥ 3.0.0
ggplot2 ≥ 2.2.1
Rdpack
Rcpp ≥0.12.15
Rglpk ≥ 0.6-1
rlang ≥ 1.0
stats

Suggests

knitr
rmarkdown
testthat
dplyr
tidyr
covr

LinkingTo

Rcpp
RcppArmadillo