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:Houjian Hou [aut, cre]

sssvcqr_0.0.3.tar.gz
sssvcqr_0.0.3.zip(r-4.7-any)sssvcqr_0.0.3.zip(r-4.6-any)sssvcqr_0.0.3.zip(r-4.5-any)
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:

On CRAN:

Conda:

4.30 score 4 scripts 259 downloads 7 exports 12 dependencies

Last updated from:186907c296. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK121
source / vignettesOK160
linux-releaseOK105
macos-releaseOK164
macos-oldrelOK178
windows-develOK74
windows-releaseOK63
windows-oldrelOK58
wasm-releaseOK106

Exports:build_graph_laplaciancv_ss_svcqrkkt_sssvcqrmake_spatial_foldsselection_recovery_tablesimulate_sssvcqr_datass_svcqr

Dependencies:clicpp11FNNglueigraphlatticelifecyclemagrittrMatrixpkgconfigrlangvctrs

Getting Started with sssvcqr
Rendered fromsssvcqr-introduction.Rnwusingknitr::knitr

Last update: 2026-05-06
Started: 2026-05-05

Lucas County Housing Example
Rendered fromlucas-county-example.Rnwusingknitr::knitr

Last update: 2026-05-06
Started: 2026-05-05