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
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lqr.pdf |lqr.html
lqr/json (API)

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

Peer review:

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

On CRAN:

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

2.08 score 1 stars 2 packages 9 scripts 420 downloads 1 mentions 16 exports 21 dependencies

Last updated 4 months agofrom:33e779ffb0. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 10 2024
R-4.5-winOKNov 10 2024
R-4.5-linuxOKNov 10 2024
R-4.4-winOKNov 10 2024
R-4.4-macOKNov 10 2024
R-4.3-winOKNov 10 2024
R-4.3-macOKNov 10 2024

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

Dependencies:BHcontfracdeSolveelliptichypergeolatticeMASSMatrixMatrixModelsMomTruncmvtnormnumDerivquantregRcppRcppArmadilloRcppEigenSparseMspatstat.univarspatstat.utilssurvivaltlrmvnmvt