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hgwrr: Hierarchical and Geographically Weighted Regression

This model divides coefficients into three types, i.e., local fixed effects, global fixed effects, and random effects (Hu et al., 2022)<doi:10.1177/23998083211063885>. If data have spatial hierarchical structures (especially are overlapping on some locations), it is worth trying this model to reach better fitness.

Version: 0.6-1
Depends: R (≥ 3.5.0), sf, stats, utils, MASS
Imports: Rcpp (≥ 1.0.8)
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), furrr, progressr
Published: 2024-11-16
DOI: 10.32614/CRAN.package.hgwrr
Author: Yigong Hu [aut, cre], Richard Harris [aut], Richard Timmerman [aut]
Maintainer: Yigong Hu <yigong.hu at bristol.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/HPDell/hgwrr/, https://hpdell.github.io/hgwrr/
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: NEWS
CRAN checks: hgwrr results

Documentation:

Reference manual: hgwrr.pdf
Vignettes: hgwrr (source, R code)

Downloads:

Package source: hgwrr_0.6-1.tar.gz
Windows binaries: r-devel: hgwrr_0.6-1.zip, r-release: hgwrr_0.6-1.zip, r-oldrel: hgwrr_0.6-1.zip
macOS binaries: r-release (arm64): hgwrr_0.6-1.tgz, r-oldrel (arm64): hgwrr_0.6-1.tgz, r-release (x86_64): hgwrr_0.6-1.tgz, r-oldrel (x86_64): hgwrr_0.6-1.tgz
Old sources: hgwrr archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=hgwrr to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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