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>).
| Version: | 0.2.0 |
| Imports: | glmnet (≥ 2.0-13), ggplot2 (≥ 2.2.1), Rdpack, Rcpp (≥ 0.12.15) |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | Rglpk (≥ 0.6-1), lpSolveAPI (≥ 5.5.2.0-17), knitr, rmarkdown, testthat, flare, igraph, dplyr, tidyr, zeallot |
| Published: | 2018-05-19 |
| Author: | Oystein Sorensen |
| Maintainer: | Oystein Sorensen <oystein.sorensen.1985 at gmail.com> |
| License: | GPL-3 |
| URL: | https://github.com/osorensen/hdme |
| NeedsCompilation: | yes |
| Citation: | hdme citation info |
| Materials: | README NEWS |
| CRAN checks: | hdme results |
| Reference manual: | hdme.pdf |
| Vignettes: |
The hdme package: regression methods for high-dimensional data with measurement error |
| Package source: | hdme_0.2.0.tar.gz |
| Windows binaries: | r-devel: hdme_0.2.0.zip, r-release: hdme_0.2.0.zip, r-oldrel: hdme_0.2.0.zip |
| OS X binaries: | r-release: hdme_0.2.0.tgz, r-oldrel: hdme_0.2.0.tgz |
| Old sources: | hdme archive |
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