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
Author: Ian Meneghel Danilevicz ORCID iD [aut, cre], Pascal Bondon [aut], Valderio A. Reisen [aut]
Maintainer: Ian Meneghel Danilevicz <iandanilevicz at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: alqrfe results


Reference manual: alqrfe.pdf


Package source: alqrfe_1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): alqrfe_1.1.tgz, r-oldrel (arm64): alqrfe_1.1.tgz, r-release (x86_64): alqrfe_1.1.tgz, r-oldrel (x86_64): alqrfe_1.1.tgz
Old sources: alqrfe archive


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