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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | BsplineQuantReg_0.1.0.tar.gz |
84.6 KiB |
0.1.0 |
rolling linux/noble R-4.5 | BsplineQuantReg_0.1.0.tar.gz |
84.7 KiB |
0.1.0 |
rolling source/ R- | BsplineQuantReg_0.1.0.tar.gz |
25.2 KiB |
0.1.0 |
latest linux/jammy R-4.5 | BsplineQuantReg_0.1.0.tar.gz |
84.6 KiB |
0.1.0 |
latest linux/noble R-4.5 | BsplineQuantReg_0.1.0.tar.gz |
84.7 KiB |
0.1.0 |
latest source/ R- | BsplineQuantReg_0.1.0.tar.gz |
25.2 KiB |
0.1.0 |
2026-04-23 source/ R- | BsplineQuantReg_0.1.0.tar.gz |
0 B |