hdme

The goal of hdme is to provide penalized regression methods for High-Dimensional Measurement Error problems (errors-in-variables).

Installation

Install hdme from CRAN using.

install.packages("hdme")

You can install the latest development version from github with:

# install.packages("devtools")
devtools::install_github("osorensen/hdme", build_vignettes = TRUE)

Dependency on Rglpk

hdme uses the Rglpk package, which requires the GLPK library package to be installed. On some platforms this requires a manual installation.

On Debian/Ubuntu, you might use:

sudo apt-get install libglpk-dev

On macOS, you might use:

brew install glpk

Methods

hdme provides implementations of the following algorithms:

The methods implemented in the package include

• Corrected Lasso for Linear Models (Loh and Wainwright (2012))
• Corrected Lasso for Generalized Linear Models (Sorensen, Frigessi, and Thoresen (2015))
• Matrix Uncertainty Selector for Linear Models (Rosenbaum and Tsybakov (2010))
• Matrix Uncertainty Selector for Generalized Linear Models (Sorensen et al. (2018))
• Matrix Uncertainty Lasso for Generalized Linear Models (Sorensen et al. (2018))
• Generalized Dantzig Selector (James and Radchenko (2009))

Contributions

Contributions to hdme are very welcome. If you have a question or suspect you have found a bug, please open an Issue. Code contribution by pull requests are also appreciated.

References