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-any)lqr_5.2.zip(r-4.6-any)lqr_5.2.zip(r-4.5-any)
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✨
DESCRIPTION
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.

2.03 score 1 stars 2 packages 18 scripts 394 downloads 1 mentions 16 exports 21 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK197
source / vignettesOK197
linux-releaseOK153
macos-releaseOK411
macos-oldrelOK138
windows-develOK127
windows-releaseOK118
windows-oldrelOK109
wasm-releaseOK110

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

Dependencies:BHcontfracdeSolveelliptichypergeolatticeMASSMatrixMatrixModelsMomTruncmvtnormnumDerivquantregRcppRcppArmadilloRcppEigenSparseMspatstat.univarspatstat.utilssurvivaltlrmvnmvt