Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
-
✓DOI references
Found 3 DOI reference(s) in README -
○Academic publication links
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (11.3%) to scientific vocabulary
Repository
R interface for HGWR
Basic Info
- Host: GitHub
- Owner: HPDell
- Language: R
- Default Branch: master
- Homepage: https://hpdell.github.io/hgwrr/
- Size: 22.5 MB
Statistics
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 1
- Releases: 3
Metadata Files
README.md
hgwrr
This package is provides R interfaces to calibrate the Hierarchical and Geographically Weighted Regression (HGWR) model.
Installation
The package now is on CRAN.
R
install.packages("hgwrr")
If you want to install the latest version from GitHub, note that the packages relies on a submodule from hpdell/hgwr. So install_github() from the devtools package is probably not working. Instead, it's better to recursively clone the package.
bash
git clone --recursive https://github.com/hpdell/hgwrr
R CMD INSTALL hgwrr
Basic Usage
Here is a quick example showing how it works.
r
library(hgwrr)
data(multisampling)
hgwr(
formula = y ~ L(g1 + g2) + x1 + (z1 | group),
data = multisampling$data,
coords = multisampling$coords,
bw = 10
)
For further information, please read this article. There is a full example.
Reference
- Hu, Yigong, Lu, Binbin, Ge, Yong, Dong, Guanpeng, 2022. Uncovering spatial heterogeneity in real estate prices via combined hierarchical linear model and geographically weighted regression. Environment and Planning B: Urban Analytics and City Science. DOI
- Yigong Hu, Richard Harris, Richard Timmerman, and Binbin Lu. A Hierarchical and Geographically Weighted Regression Model and Its Backfitting Maximum Likelihood Estimator (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 39:1-39:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) DOI
Owner
- Name: Yigong Hu
- Login: HPDell
- Kind: user
- Location: Bristol, UK
- Company: University of Bristol
- Website: https://hpdell.github.io/
- Repositories: 61
- Profile: https://github.com/HPDell
A PhD student in University of Bristol. Have great interest in programming and mathematics. Working on GWmodel and GIS.
GitHub Events
Total
- Create event: 8
- Release event: 1
- Issues event: 2
- Watch event: 1
- Delete event: 10
- Push event: 30
- Pull request event: 15
- Fork event: 1
Last Year
- Create event: 8
- Release event: 1
- Issues event: 2
- Watch event: 1
- Delete event: 10
- Push event: 30
- Pull request event: 15
- Fork event: 1
Packages
- Total packages: 1
-
Total downloads:
- cran 568 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 8
- Total maintainers: 1
cran.r-project.org: hgwrr
Hierarchical and Geographically Weighted Regression
- Homepage: https://github.com/HPDell/hgwrr/
- Documentation: http://cran.r-project.org/web/packages/hgwrr/hgwrr.pdf
- License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
-
Latest release: 0.6-1
published over 1 year ago
Rankings
Maintainers (1)
Dependencies
- actions/checkout v3 composite
- actions/checkout v2 composite
- actions/download-artifact v3 composite
- actions/upload-artifact v3 composite
- docker://ghcr.io/hpdell/hgwr-ubuntu-docker-action latest composite
- r-lib/actions/check-r-package v2 composite
- r-lib/actions/setup-r v2 composite
- r-lib/actions/setup-r-dependencies v2 composite
- softprops/action-gh-release v1 composite
- R >= 3.5.0 depends
- sf * depends
- stats * depends
- utils * depends
- Rcpp >= 1.0.8 imports
- methods * imports
- testthat >= 3.0.0 suggests