Package: hgwrr
Type: Package
Title: Hierarchical and Geographically Weighted Regression
Version: 0.6-2
Date: 2025-09-24
Authors@R: c(person(given = "Yigong",
                    family = "Hu",
                    role = c("aut", "cre"),
                    email = "yigong.hu@bristol.ac.uk"),
             person(given = "Richard",
                    family = "Harris",
                    role = "aut"),
             person(given = "Richard",
                    family = "Timmerman",
                    role = "aut"))
Maintainer: Yigong Hu <yigong.hu@bristol.ac.uk>
Description: 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.
License: GPL (>= 2)
URL: https://github.com/HPDell/hgwrr/, https://hpdell.github.io/hgwrr/
Imports: Rcpp (>= 1.0.8)
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 3.5.0), sf, stats, utils, MASS
NeedsCompilation: yes
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), furrr, progressr,
SystemRequirements: GNU make
RoxygenNote: 7.2.3
VignetteBuilder: knitr
Config/Needs/website: tidyverse, ggplot2, tmap, lme4, spdep, GWmodel
Packaged: 2025-09-24 11:07:59 UTC; yigong
Author: Yigong Hu [aut, cre],
  Richard Harris [aut],
  Richard Timmerman [aut]
Repository: CRAN
Date/Publication: 2025-09-28 05:20:28 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-28 04:56:20 UTC; unix
Archs: hgwrr.so.dSYM
