https://tournefeuille2026.r-universe.devRecent package updates in tournefeuille2026R-universehttps://github.com/tournefeuille2026.pnghttps://tournefeuille2026.r-universe.devSat, 10 Oct 2026 19:14:59 GMTalexandre.abbes@proton.me (Alexandre Abbes)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 (2025)' <doi:10.5281/zenodo.17427913>. Other formulations are simple consequences of the other given references. All B-spline and polynomial functions have been rewritten for consistency. This package provides an original B-spline library for conversion between PP-form and B-spline representation, evaluation, differentiation, callable and non-callable objects, print human readable pp forms, view basis, all based on "De Boor\'s" theory. It also extends to multiple knots to catch up singularities. This feature is robust in the package including for constrained regression. This R implementation is intended for demonstration and prototyping. An equivalent Python package is available at <https://pypi.org/project/BsplineQuantRegpy/>.https://github.com/r-universe/alexandreabbes/actions/runs/38079199909Sat, 10 Oct 2026 19:14:59 GMTBsplineQuantReg0.2.6successhttps://alexandreabbes.r-universe.devhttps://github.com/alexandreabbes/bsplinequantregbspline_basis_manipulation.Rmdbspline_basis_manipulation.htmlB-spline Basis Manipulation2026-08-08 20:35:132026-10-07 17:06:11introduction.Rmdintroduction.htmlIntroduction2026-08-07 07:25:452026-10-10 19:14:59polynomial_library.Rmdpolynomial_library.htmlPolynomial Library in BsplineQuantReg2026-08-08 20:35:132026-10-10 16:26:55shape_constraints.Rmdshape_constraints.htmlShape Constraints with BsplineQuantReg2026-08-07 07:25:452026-10-10 16:26:55theoretical_background.Rmdtheoretical_background.htmlTheoretical Background2026-08-09 22:11:482026-10-10 16:26:55alexandre.abbes@proton.me (Alexandre Abbes)A user-friendly interactive Shiny interface for the 'BsplineQuantReg' package, enabling quantile regression using B-splines with shape constraints, based on the method described in Abbes (2025). Almost all parameters of the main function 'quantile_spline()' can be tuned. Features include interactive knot placement, per-region constraint specification, 'CSV' data import, direct demo access, reproducible R code generation, and solver selection. The version 0.2.2 handles knots multiplicity, Bspline basis visualisation, mean-square regression, pp form visualisation under human readable form, in local or canonical bases, The GUI provides two modes, basic (compatible with 'BsplineQuantReg' >= 0.2.2) and advanced (requires 'BsplineQuantReg' >= 0.2.5 for stable multiplicity features). This GUI an improved version of the 'Python Tk' version of 'BsplineQuantRegPy'.https://github.com/r-universe/tournefeuille2026/actions/runs/38072273756Tue, 01 Sep 2026 08:50:15 GMTBsplineQuantRegGui0.2.2successhttps://tournefeuille2026.r-universe.devhttps://github.com/cran/BsplineQuantRegGui