Package: lqr 5.1

Christian E. Galarza

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_5.1.tar.gz
lqr_5.1.tar.gz(r-4.5-noble)lqr_5.1.tar.gz(r-4.4-noble)
lqr_5.1.tgz(r-4.4-emscripten)lqr_5.1.tgz(r-4.3-emscripten)
lqr.pdf |lqr.html
lqr/json (API)

# Installlqr in R:
install.packages('lqr',repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • ais - Australian institute of sport data
  • resistance - Tumor-cell resistance to death

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

16 exports 1 stars 0.91 score 21 dependencies 2 dependents 383 downloads

Last updated 7 days agofrom:6afa7e74fd

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

Dependencies:BHcontfracdeSolveelliptichypergeolatticeMASSMatrixMatrixModelsMomTruncmvtnormnumDerivquantregRcppRcppArmadilloRcppEigenSparseMspatstat.univarspatstat.utilssurvivaltlrmvnmvt