BsplineQuantReg: 'Constrained Quantile Regression with B-Splines'
Quantile regression with B-splines under shape constraints.
The initial version with cubic splines is now augmented with splines
of degree 1 to 4. Constraints for degrees 3 (monotone) and 4
(monotone and convex) use the Karlin-Studden SOCP characterization
for the sign of the polynomial, while other constraints applied
at the knots are added as linear problems. The method for cubic
splines is described in Abbes (2026) <doi:10.5281/zenodo.17427913>.
Other formulations are simple consequences of the other given
references. This R implementation is intended for demonstration
and prototyping. All B-spline and polynomial functions have been
rewritten for consistency. An equivalent Python package is available
at <https://pypi.org/project/BsplineQuantRegpy/>.
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