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 Description: This model divides coefficients into three types, i.e., local fixed effects, global fixed effects, and random effects (Hu et al., 2022). 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 Roxygen: list(markdown = TRUE) RoxygenNote: 7.2.3 VignetteBuilder: knitr Config/Needs/website: tidyverse, ggplot2, tmap, lme4, spdep, GWmodel Config/pak/sysreqs: libabsl-dev cmake libgdal-dev gdal-bin libgeos-dev make libssl-dev libproj-dev libsqlite3-dev libudunits2-dev Repository: https://hpdell.r-universe.dev Date/Publication: 2026-04-21 08:18:02 UTC RemoteUrl: https://github.com/hpdell/hgwrr RemoteRef: HEAD RemoteSha: 27376766a9c4b9aadb2b6362f2847424c13d490e Packaged: 2026-06-20 07:09:42 UTC; root Author: Yigong Hu [aut, cre], Richard Harris [aut], Richard Timmerman [aut]