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.

Version:	0.0.4
Depends:	R (≥ 4.1)
Imports:	FNN, igraph, Matrix, methods, stats
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-05-15
DOI:	10.32614/CRAN.package.sssvcqr
Author:	Houjian Hou [aut, cre]
Maintainer:	Houjian Hou <beidaihe77 at qq.com>
BugReports:	https://github.com/Stork343/sssvcqr/issues
License:	GPL (≥ 3)
URL:	https://github.com/Stork343/sssvcqr
NeedsCompilation:	no
Citation:	sssvcqr citation info
Materials:	README, NEWS
CRAN checks:	sssvcqr results

Documentation:

Reference manual:	sssvcqr.html , sssvcqr.pdf
Vignettes:	Lucas County Housing Example (source, R code) Getting Started with sssvcqr (source, R code)

Downloads:

Package source:	sssvcqr_0.0.4.tar.gz
Windows binaries:	r-devel: sssvcqr_0.0.4.zip, r-release: not available, r-oldrel: sssvcqr_0.0.4.zip
macOS binaries:	r-release (arm64): sssvcqr_0.0.4.tgz, r-oldrel (arm64): sssvcqr_0.0.4.tgz, r-release (x86_64): sssvcqr_0.0.4.tgz, r-oldrel (x86_64): sssvcqr_0.0.4.tgz

Linking:

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