hdme: 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) <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>).

Package details

AuthorOystein Sorensen
MaintainerOystein Sorensen <oystein.sorensen.1985@gmail.com>
URL https://github.com/osorensen/hdme
Package repositoryView on CRAN
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hdme documentation built on July 2, 2020, 4:15 a.m.