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)
The goal of hdme is to provide penalized regression methods for High-Dimensional Measurement Error problems (errors-in-variables).
hdme from CRAN using.
You can install the latest development version from github with:
Rglpk is suggested when installing
hdme. In order to
Rglpk on macOS, you may need to first install
issuing the following statement on the command line:
brew install glpk
If you are not able to install
Rglpk, then please install the
lpSolveAPI instead, using the command
The functions in
hdme that use
Rglpk, will switch to
automatically if the former is not available.
hdme provides implementations of the following algorithms:
The methods implemented in the package include
James, Gareth M., and Peter Radchenko. 2009. “A Generalized Dantzig Selector with Shrinkage Tuning.” Biometrika 96 (2): 323–37.
Loh, Po-Ling, and Martin J. Wainwright. 2012. “High-Dimensional Regression with Noisy and Missing Data: Provable Guarantees with Nonconvexity.” Ann. Statist. 40 (3). The Institute of Mathematical Statistics: 1637–64.
Rosenbaum, Mathieu, and Alexandre B. Tsybakov. 2010. “Sparse Recovery Under Matrix Uncertainty.” Ann. Statist. 38 (5): 2620–51.
Sorensen, Oystein, Arnoldo Frigessi, and Magne Thoresen. 2015. “Measurement Error in Lasso: Impact and Likelihood Bias Correction.” Statistica Sinica 25 (2). Institute of Statistical Science, Academia Sinica: 809–29.
Sorensen, Oystein, Kristoffer Herland Hellton, Arnoldo Frigessi, and Magne Thoresen. 2018. “Covariate Selection in High-Dimensional Generalized Linear Models with Measurement Error.” Journal of Computational and Graphical Statistics. Taylor & Francis.
Fixed random number seed issue which caused test to fail in R-devel.
Internal fix to
cv_corrected_lasso. Got rid of duplicated code by calling the function
Rglpk does not install automatically on macOS, this package was moved from Imports to Suggests. In addition,
lpSolveAPI was added to Suggests. This means that the package should build also on systems that do not have
Rglpk, in particular the versions of macOS on CRAN.
The changes involved adding an optional linear solver from
lpSolveAPI in the function
plot.gds function, which plots the coefficients estimated by
Internal adjustment, which removed importing of external packages into the namespace, and instead specified the functions explicitly using
tidyverse has been removed from Suggests field
tidyr have been added instead. Similarly,
library(tidyverse) in the vignette has been replaced by
hdme is now on CRAN.