hdme (0.3.3)

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High-Dimensional Regression with Measurement Error.


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) ). 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) ).

Maintainer: Oystein Sorensen
Author(s): Oystein Sorensen

License: GPL-3

Uses: ggplot2, glmnet, Rcpp, Rdpack, Rglpk, testthat, knitr, dplyr, tidyr, rmarkdown, covr

Released 8 days ago.

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