Package: EXRQ 1.0

EXRQ: Extreme Regression of Quantiles

Estimation for high conditional quantiles based on quantile regression.

Authors:Huixia Judy Wang

EXRQ_1.0.tar.gz
EXRQ_1.0.zip(r-4.5)EXRQ_1.0.zip(r-4.4)EXRQ_1.0.zip(r-4.3)
EXRQ_1.0.tgz(r-4.4-any)EXRQ_1.0.tgz(r-4.3-any)
EXRQ_1.0.tar.gz(r-4.5-noble)EXRQ_1.0.tar.gz(r-4.4-noble)
EXRQ_1.0.tgz(r-4.4-emscripten)EXRQ_1.0.tgz(r-4.3-emscripten)
EXRQ.pdf |EXRQ.html✨
EXRQ/json (API)

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

Peer review:

On CRAN:

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

10 exports 0.00 score 8 dependencies 10 scripts 437 downloads

Last updated 8 years agofrom:cfaff6808a. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 20 2024
R-4.5-winOKAug 20 2024
R-4.5-linuxOKAug 20 2024
R-4.4-winOKAug 20 2024
R-4.4-macOKAug 20 2024
R-4.3-winOKAug 20 2024
R-4.3-macOKAug 20 2024

Exports:est.gamma.funcEstc.funcEVI.CFG.funcPowT.1tau.funcqparetorparetoselect.k.functestC.EVIThreeStageTwoStage

Dependencies:latticeMASSMatrixMatrixModelsmnormtquantregSparseMsurvival