Package: BsplineQuantReg 0.1.0

Alexandre Abbes

BsplineQuantReg: 'Constrained Quantile Regression with Cubic B-Splines'

Quantile regression with cubic B-splines under monotonicity and convexity constraints using the Karlin-Studden SOCP formulation. The method is described in Abbes (2026) <doi:10.5281/zenodo.17427913>. This R implementation is intended for demonstration and prototyping; all B-spline and polynomial functions have been rewritten for consistency. A faster version written in 'Python' is available at <https://github.com/alexandreabbes/Constrained-Quantile-Regression-with-cubic-splines>.

Authors:Alexandre Abbes [aut, cre]

BsplineQuantReg_0.1.0.tar.gz
BsplineQuantReg_0.1.0.tar.gz(r-4.6-any)
BsplineQuantReg_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BsplineQuantReg/json (API)

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

Bug tracker:https://github.com/alexandreabbes/bsplinequantreg/issues

On CRAN:

Conda:

1.70 score 18 exports 15 dependencies

Last updated from:493e11b6a5. Checks:1 FAIL, 3 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64FAIL400
source / vignettesOK176
linux-release-x86_64OK174
wasm-releaseOK299

Exports:apply_karlin_constraintsbs_directBspline_baseBspline_derivbspline_to_deriv_coeffs_ppchange_polynomial_base_tayloris_betapackage_versionpoly_evalpolyaddpolyderivpolymulreduce_polSpline_der_knotsspline_evalSplineConstQuantRegBs3test_karlin_simpleview_basis

Dependencies:backportscheckmateclarabelcliCVXRgmphighslatticeMatrixosqpRcppRcppEigenS7scsslam