Package: pqrfe 1.3

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_1.3.tar.gz
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pqrfe_1.3.tar.gz(r-4.7-arm64)pqrfe_1.3.tar.gz(r-4.7-x86_64)pqrfe_1.3.tar.gz(r-4.6-arm64)pqrfe_1.3.tar.gz(r-4.6-x86_64)
pqrfe_1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
pqrfe/json (API)

# Install 'pqrfe' in R:
install.packages('pqrfe', repos = c('https://iandanilevicz.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

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

cpp

1.60 score 2 stars 1 scripts 273 downloads 4 exports 3 dependencies

Last updated from:e9be905cca. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK107
linux-devel-x86_64OK119
source / vignettesOK215
linux-release-arm64OK137
linux-release-x86_64OK149
macos-release-arm64OK84
macos-release-x86_64OK253
macos-oldrel-arm64OK108
macos-oldrel-x86_64OK271
windows-devel-arm64OK224
windows-devel-x86_64OK129
windows-release-arm64OK194
windows-release-x86_64OK92
windows-oldrel-x86_64OK90
wasm-releaseOK92

Exports:clean_datampqrplot_tauspqr

Dependencies:MASSRcppRcppArmadillo