Nothing
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>).
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Oystein Sorensen [aut, cre] (<https://orcid.org/0000-0003-0724-3542>) |
| Maintainer | Oystein Sorensen <oystein.sorensen.1985@gmail.com> |
| License | GPL-3 |
| Version | 0.6.0 |
| URL | https://github.com/osorensen/hdme |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the hdme package in your browser
Any scripts or data that you put into this service are public.
