| Port variant | std |
| Summary | Convolution-Type Smoothed Quantile Regression |
| BROKEN | |
| Package version | 1.3.3 |
| Homepage | https://github.com/XiaoouPan/conquer |
| Keywords | cran |
| Maintainer | CRAN Automaton |
| License | Not yet specified |
| Other variants | There are no other variants. |
| Ravenports | Buildsheet | History |
| Ravensource | Port Directory | History |
| Last modified | 09 AUG 2024, 21:24:17 UTC |
| Port created | 10 JUL 2020, 12:51:37 UTC |
| single | conquer: Convolution-Type Smoothed Quantile Regression Estimation and inference for conditional linear quantile regression models using a convolution smoothed approach. In the low-dimensional setting, efficient gradient-based methods are employed for fitting both a single model and a regression process over a quantile range. Normal-based and (multiplier) bootstrap confidence intervals for all slope coefficients are constructed. In high dimensions, the conquer method is complemented with flexible types of penalties (Lasso, elastic-net, group lasso, sparse group lasso, scad and mcp) to deal with complex low-dimensional structures. |
| Build (only) |
gmake:primary:std R:primary:std icu:dev:std |
| Build and Runtime |
R-Rcpp:single:std R-matrixStats:single:std R-RcppArmadillo:single:std |
| Runtime (only) |
R:primary:std R:nls:std |
| main | mirror://CRAN/src/contrib https://loki.dragonflybsd.org/cranfiles/ |
| No other ports depend on this one. |