Package: fastkqr 1.0.0

fastkqr: A Fast Algorithm for Kernel Quantile Regression

An efficient algorithm to fit and tune kernel quantile regression models based on the majorization-minimization (MM) method. It can also fit multiple quantile curves simultaneously without crossing.

Authors:Qian Tang [aut, cre], Yuwen Gu [aut], Boxiang Wang [aut]

fastkqr_1.0.0.tar.gz
fastkqr_1.0.0.zip(r-4.5)fastkqr_1.0.0.zip(r-4.4)fastkqr_1.0.0.zip(r-4.3)
fastkqr_1.0.0.tgz(r-4.4-x86_64)fastkqr_1.0.0.tgz(r-4.4-arm64)fastkqr_1.0.0.tgz(r-4.3-x86_64)fastkqr_1.0.0.tgz(r-4.3-arm64)
fastkqr_1.0.0.tar.gz(r-4.5-noble)fastkqr_1.0.0.tar.gz(r-4.4-noble)
fastkqr_1.0.0.tgz(r-4.4-emscripten)fastkqr_1.0.0.tgz(r-4.3-emscripten)
fastkqr.pdf |fastkqr.html
fastkqr/json (API)

# Install 'fastkqr' in R:
install.packages('fastkqr', repos = c('https://qiantang0326.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • fortran– Runtime library for GNU Fortran applications

On CRAN:

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

2.00 score 512 downloads 4 exports 5 dependencies

Last updated 6 months agofrom:80a6e89af8. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 11 2024
R-4.5-win-x86_64NOTENov 11 2024
R-4.5-linux-x86_64NOTENov 11 2024
R-4.4-win-x86_64NOTENov 11 2024
R-4.4-mac-x86_64NOTENov 11 2024
R-4.4-mac-aarch64NOTENov 11 2024
R-4.3-win-x86_64NOTENov 11 2024
R-4.3-mac-x86_64NOTENov 11 2024
R-4.3-mac-aarch64NOTENov 11 2024

Exports:cv.kqrcv.nckqrkqrnckqr

Dependencies:dotCall64latticeMASSMatrixrlang

Getting started with fastkqr

Rendered fromfastkqr.Rmdusingknitr::rmarkdownon Nov 11 2024.

Last update: 2024-05-14
Started: 2024-05-14