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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.
Getting started
Browse package contents
Package details |
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| Author | Yigong Hu [aut, cre], Richard Harris [aut], Richard Timmerman [aut] |
| Maintainer | Yigong Hu <yigong.hu@bristol.ac.uk> |
| License | GPL (>= 2) |
| Version | 0.6-1 |
| URL | https://github.com/HPDell/hgwrr/ https://hpdell.github.io/hgwrr/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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