Package: sssvcqr 0.0.3
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.
Authors:
sssvcqr_0.0.3.tar.gz
sssvcqr_0.0.3.zip(r-4.7)sssvcqr_0.0.3.zip(r-4.6)sssvcqr_0.0.3.zip(r-4.5)
sssvcqr_0.0.3.tgz(r-4.6-any)sssvcqr_0.0.3.tgz(r-4.5-any)
sssvcqr_0.0.3.tar.gz(r-4.7-any)sssvcqr_0.0.3.tar.gz(r-4.6-any)
sssvcqr_0.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
sssvcqr/json (API)
| # Install 'sssvcqr' in R: |
| install.packages('sssvcqr', repos = c('https://stork343.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/stork343/sssvcqr/issues
Datasets:
- lucas_housing_sample - Lucas County housing sample
Last updated from:c32ee90a8f. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 118 | ||
| source / vignettes | OK | 157 | ||
| linux-release-x86_64 | OK | 109 | ||
| macos-release-arm64 | OK | 164 | ||
| macos-oldrel-arm64 | OK | 203 | ||
| windows-devel | OK | 84 | ||
| windows-release | OK | 81 | ||
| windows-oldrel | OK | 76 | ||
| wasm-release | OK | 101 |
Exports:build_graph_laplaciancv_ss_svcqrkkt_sssvcqrmake_spatial_foldsselection_recovery_tablesimulate_sssvcqr_datass_svcqr
Dependencies:clicpp11FNNglueigraphlatticelifecyclemagrittrMatrixpkgconfigrlangvctrs
Getting Started with sssvcqr
Last update: 2026-05-06
Started: 2026-05-05
Lucas County Housing Example
Last update: 2026-05-06
Started: 2026-05-05
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Sparse-Smooth Spatially Varying Coefficient Quantile Regression | sssvcqr-package sssvcqr |
| Build a weighted k-nearest-neighbor graph Laplacian | build_graph_laplacian |
| Spatially blocked cross-validation for SS-SVCQR | cv_ss_svcqr |
| KKT diagnostics for an SS-SVCQR fit | kkt_sssvcqr |
| Lucas County housing sample | lucas_housing_sample |
| Create spatial cross-validation folds | make_spatial_folds |
| Plot an SS-SVCQR fit | plot.sssvcqr |
| Predict from an SS-SVCQR fit | predict.sssvcqr |
| Compare true and estimated spatial-deviation selection | selection_recovery_table |
| Simulate data for SS-SVCQR examples | simulate_sssvcqr_data |
| Fit sparse-smooth spatially varying coefficient quantile regression | ss_svcqr |
