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).
- Version0.6.0
- R versionunknown
- LicenseGPL-3
- Needs compilation?Yes
- hdme citation info
- Last release05/16/2023
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Team
Oystein Sorensen
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- Imports6 packages
- Suggests6 packages
- Linking To2 packages