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alqrfe: Adaptive Lasso Quantile Regression with Fixed Effects
Quantile regression with fixed effects solves longitudinal data, considering the individual intercepts as fixed effects. The parametric set of this type of problem used to be huge. Thus penalized methods such as Lasso are currently applied. Adaptive Lasso presents oracle proprieties, which include Gaussianity and correct model selection. Bayesian information criteria (BIC) estimates the optimal tuning parameter lambda. Plot tools are also available.
| Version: |
1.1 |
| Imports: |
Rcpp (≥ 1.0.5), MASS (≥ 7.3-49) |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Published: |
2022-11-30 |
| DOI: |
10.32614/CRAN.package.alqrfe |
| Author: |
Ian Meneghel Danilevicz
 [aut, cre],
Pascal Bondon [aut],
Valderio A. Reisen [aut] |
| Maintainer: |
Ian Meneghel Danilevicz <iandanilevicz at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| CRAN checks: |
alqrfe results |
Documentation:
Downloads:
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https://CRAN.R-project.org/package=alqrfe
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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