Package: lqr 5.2

lqr: Robust Linear Quantile Regression

It fits a robust linear quantile regression model using a new family of zero-quantile distributions for the error term. Missing values and censored observations can be handled as well. This family of distribution includes skewed versions of the Normal, Student's t, Laplace, Slash and Contaminated Normal distribution. It also performs logistic quantile regression for bounded responses as shown in Galarza et.al.(2020) <doi:10.1007/s13571-020-00231-0>. It provides estimates and full inference. It also provides envelopes plots for assessing the fit and confidences bands when several quantiles are provided simultaneously.

Authors:Christian E. Galarza <[email protected]>, Luis Benites <[email protected]>, Marcelo Bourguignon <[email protected]>, Victor H. Lachos <[email protected]>

lqr_5.2.tar.gz
lqr_5.2.zip(r-4.7)lqr_5.2.zip(r-4.6)lqr_5.2.zip(r-4.5)
lqr_5.2.tgz(r-4.6-any)lqr_5.2.tgz(r-4.5-any)
lqr_5.2.tar.gz(r-4.7-any)lqr_5.2.tar.gz(r-4.6-any)
lqr_5.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
lqr/json (API)

# Install 'lqr' in R:
install.packages('lqr', repos = c('https://chedgala.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • ais - Australian institute of sport data
  • resistance - Tumor-cell resistance to death

On CRAN:

Conda:

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

1.78 score 1 stars 2 packages 9 scripts 355 downloads 1 mentions 16 exports 21 dependencies

Last updated from:33e779ffb0. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK167
source / vignettesOK260
linux-release-x86_64OK215
macos-release-arm64OK124
macos-oldrel-arm64OK112
windows-develOK110
windows-releaseOK121
windows-oldrelOK102
wasm-releaseOK123

Exports:best.lqrcens.lqrdSKDdtruncEgigextruncLog.best.lqrLog.lqrlqrpSKDptruncqSKDqtruncrSKDrtruncvartrunc

Dependencies:BHcontfracdeSolveelliptichypergeolatticeMASSMatrixMatrixModelsMomTruncmvtnormnumDerivquantregRcppRcppArmadilloRcppEigenSparseMspatstat.univarspatstat.utilssurvivaltlrmvnmvt