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>).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.6.0 |
rolling source/ R- | hdme_0.6.0.tar.gz |
377.6 KiB |
0.6.0 |
rolling linux/jammy R-4.5 | hdme_0.6.0.tar.gz |
463.3 KiB |
0.6.0 |
rolling linux/noble R-4.5 | hdme_0.6.0.tar.gz |
464.8 KiB |
0.6.0 |
latest source/ R- | hdme_0.6.0.tar.gz |
377.6 KiB |
0.6.0 |
latest linux/jammy R-4.5 | hdme_0.6.0.tar.gz |
463.3 KiB |
0.6.0 |
latest linux/noble R-4.5 | hdme_0.6.0.tar.gz |
464.8 KiB |
0.6.0 |
2026-04-23 source/ R- | hdme_0.6.0.tar.gz |
377.6 KiB |
0.6.0 |
2026-04-09 windows/windows R-4.5 | hdme_0.6.0.zip |
787.1 KiB |
0.6.0 |
2025-04-20 source/ R- | hdme_0.6.0.tar.gz |
377.6 KiB |