'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/.