hdqr - Fast Algorithm for Penalized Quantile Regression
Implements an efficient algorithm to fit and tune penalized quantile regression models using the generalized coordinate descent algorithm. Designed to handle high-dimensional datasets effectively, with emphasis on precision and computational efficiency. This package implements the algorithms proposed in Tang, Q., Zhang, Y., & Wang, B. (2022) <https://openreview.net/pdf?id=RvwMTDYTOb>.
Last updated 28 days ago
fortran
2.30 score 10 downloadsfastkqr - A Fast Algorithm for Kernel Quantile Regression
An efficient algorithm to fit and tune kernel quantile regression models based on the majorization-minimization (MM) method. It can also fit multiple quantile curves simultaneously without crossing.
Last updated 10 months ago
fortranopenblas
2.00 score 576 downloads