| hgwrr-package {hgwrr} | R Documentation |
HGWR: Hierarchical and Geographically Weighted Regression
Description
An R and C++ implementation of Hierarchical and Geographically Weighted Regression (HGWR) model is provided in this package. This model divides coefficients into three types: local fixed effects, global fixed effects, and random effects. If data have spatial hierarchical structures (especially are overlapping on some locations), it is worth trying this model to reach better fitness.
Details
The DESCRIPTION file:
| Package: | hgwrr |
| Type: | Package |
| Title: | Hierarchical and Geographically Weighted Regression |
| Version: | 0.3-0 |
| Date: | 2023-05-24 |
| Author: | Yigong Hu, Richard Harris, Richard Timmerman |
| 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/hgwr/, https://hpdell.github.io/hgwr/ |
| Imports: | Rcpp (>= 1.0.8) |
| LinkingTo: | Rcpp, RcppArmadillo |
| Depends: | R (>= 3.5.0), stats, utils |
| SystemRequirements: | GNU make |
| Roxygen: | list(markdown = TRUE) |
| RoxygenNote: | 7.2.3 |
Index of help topics:
coef.hgwrm Get estimated coefficients.
fitted.hgwrm Get fitted reponse.
hgwr Hierarchical and Geographically Weighted
Regression
hgwrr-package HGWR: Hierarchical and Geographically Weighted
Regression
matrix2char Convert a numeric matrix to character matrix
according to a format string.
multisampling Simulated Spatial Multisampling Data
(DataFrame)
multisampling.large Large Scale Simulated Spatial Multisampling
Data (DataFrame)
parse.formula Parse a HGWR formula.
print.hgwrm Print description of a 'hgwrm' object.
print.summary.hgwrm Print summary of an 'hgwrm' object.
print.table.md Print a character matrix as a table.
residuals.hgwrm Get residuals.
summary.hgwrm Summary an 'hgwrm' object.
wuhan.hp Wuhan Second-hand House Price and POI Data
(DataFrame)
Author(s)
Yigong Hu, Richard Harris, Richard Timmerman
Maintainer: Yigong Hu <yigong.hu@bristol.ac.uk>
References
Hu, Y., Lu, B., Ge, Y., Dong, G., 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: 10.1177/23998083211063885.