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hdme  

High-Dimensional Regression with Measurement Error
View on CRAN: Click here


Download and install hdme package within the R console
Install from CRAN:
install.packages("hdme")

Install from Github:
library("remotes")
install_github("cran/hdme")

Install by package version:
library("remotes")
install_version("hdme", "0.6.0")



Attach the package and use:
library("hdme")
Maintained by
Oystein Sorensen
[Scholar Profile | Author Map]
First Published: 2018-03-09
Latest Update: 2023-05-16
Description:
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) ).
How to cite:
Oystein Sorensen (2018). hdme: High-Dimensional Regression with Measurement Error. R package version 0.6.0, https://cran.r-project.org/web/packages/hdme. Accessed 03 May. 2025.
Previous versions and publish date:
0.1.0 (2018-03-09 13:54), 0.1.1 (2018-03-30 18:48), 0.2.0 (2018-05-19 12:31), 0.2.1 (2018-10-15 15:00), 0.2.2 (2019-03-07 07:50), 0.2.3 (2019-04-12 12:03), 0.3.1 (2019-05-20 18:50), 0.3.2 (2019-11-11 09:50), 0.3.3 (2020-05-18 14:50), 0.3.4 (2021-09-02 06:30), 0.4.0 (2022-07-03 22:30), 0.5.0 (2022-07-20 15:30), 0.5.1 (2023-02-28 10:22)
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Complete documentation for hdme
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