Package: pqrfe 1.1

pqrfe: Penalized Quantile Regression with Fixed Effects

Quantile regression with fixed effects is a general model for longitudinal data. Here we proposed to solve it by several methods. The estimation methods include three loss functions as check, asymmetric least square and asymmetric Huber functions; and three structures as simple regression, fixed effects and fixed effects with penalized intercepts by LASSO.

Authors:Ian Meneghel Danilevicz [aut, cre], Valderio A Reisen [aut], Pascal Bondon [aut]

pqrfe_1.1.tar.gz
pqrfe_1.1.zip(r-4.5)pqrfe_1.1.zip(r-4.4)pqrfe_1.1.zip(r-4.3)
pqrfe_1.1.tgz(r-4.4-x86_64)pqrfe_1.1.tgz(r-4.4-arm64)pqrfe_1.1.tgz(r-4.3-x86_64)pqrfe_1.1.tgz(r-4.3-arm64)
pqrfe_1.1.tar.gz(r-4.5-noble)pqrfe_1.1.tar.gz(r-4.4-noble)
pqrfe_1.1.tgz(r-4.4-emscripten)pqrfe_1.1.tgz(r-4.3-emscripten)
pqrfe.pdf |pqrfe.html
pqrfe/json (API)

# Install 'pqrfe' in R:
install.packages('pqrfe', repos = c('https://iandanilevicz.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

35 exports 1 stars 0.09 score 3 dependencies 205 downloads

Last updated 2 years agofrom:2cf24488b5. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 22 2024
R-4.5-win-x86_64NOTEAug 22 2024
R-4.5-linux-x86_64NOTEAug 22 2024
R-4.4-win-x86_64NOTEAug 22 2024
R-4.4-mac-x86_64NOTEAug 22 2024
R-4.4-mac-aarch64NOTEAug 22 2024
R-4.3-win-x86_64NOTEAug 22 2024
R-4.3-mac-x86_64NOTEAug 22 2024
R-4.3-mac-aarch64NOTEAug 22 2024

Exports:check_lambdachoice_pclean_datad_psi_alsd_psi_mqf_denf_tabloss_erloss_erfeloss_erlassoloss_mqrloss_mqrfeloss_mqrlassoloss_qrloss_qrfeloss_qrlassompqroptim_eroptim_erfeoptim_erlassooptim_mqroptim_mqrfeoptim_mqrlassooptim_qroptim_qrfeoptim_qrlassoplot_tauspqrprint.PQRpsi_alspsi_mqq_covrho_koenkerrho_mqsgf

Dependencies:MASSRcppRcppArmadillo