sssvcqr
Sparse-Smooth Spatially Varying Coefficient Quantile Regression
Implements sparse-smooth spatially varying coefficient quantile regression (SS-SVCQR), combining quantile regression of Koenker and Bassett (1978) <doi:10.2307/1913643>, grouped variable selection of Yuan and Lin (2006) <doi:10.1111/j.1467-9868.2005.00532.x>, graph regularization, and the alternating direction method of multipliers of Boyd et al. (2011) <doi:10.1561/2200000016>. The package provides graph-regularized estimation, spatially blocked cross-validation, prediction, diagnostics, and simulation helpers for global-local spatial quantile regression.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.0.4 |
rolling linux/noble R-4.5 | sssvcqr_0.0.4.tar.gz |
1.3 MiB |
0.0.4 |
rolling source/ R- | sssvcqr_0.0.4.tar.gz |
1.3 MiB |
0.0.4 |
rolling linux/jammy R-4.5 | sssvcqr_0.0.4.tar.gz |
1.3 MiB |
0.0.4 |
latest linux/jammy R-4.5 | sssvcqr_0.0.4.tar.gz |
1.3 MiB |
0.0.4 |
latest linux/noble R-4.5 | sssvcqr_0.0.4.tar.gz |
1.3 MiB |
0.0.4 |
latest source/ R- | sssvcqr_0.0.4.tar.gz |
1.3 MiB |
0.0.4 |
2026-04-23 source/ R- | sssvcqr_0.0.4.tar.gz |
0 B |