Share and Export
Share and Export
Lu, Binbin, Brunsdon, Chris, Charlton, Martin and Harris, Paul (2019) A response to ‘A comment on geographically weighted regression with parameter-specific distance metrics’. International Journal of Geographical Information Science, 33 (7). pp. 1300-1312. ISSN 1365-8816
Preview
CB-Response-2019.pdf
Download (1MB) | Preview
Abstract
In this article, we respond to ‘A comment on geographically weighted regression with parameter-specific distance metrics’ by Oshan et al. (2019), published in this journal, where several concerns on the parameter-specific distance metric geographically weighted regression (PSDM GWR) technique are raised. In doing so, we review the developmental timeline of the multiscale geographically weighed regression modelling framework with related and equivalent models, including flexible bandwidth GWR, conditional GWR and PSDM GWR. In our response, we have tried to answer all the concerns raised in terms of applicability, veracity, interpretability and computational efficiency of the PSDM GWR model.
| Item Type: | Article |
|---|---|
| Additional Information: | Cite as: Binbin Lu, Chris Brunsdon, Martin Charlton & Paul Harris (2019) A response to ‘A comment on geographically weighted regression with parameter-specific distance metrics’, International Journal of Geographical Information Science, 33:7, 1300-1312, DOI: 10.1080/13658816.2019.1585541 |
| Keywords: | Multiscale; GWmodel; local regression; spatial heterogeneity; GWR; |
| Academic Unit: | Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG Faculty of Social Sciences > Geography Faculty of Social Sciences > Research Institutes > Maynooth University Social Sciences Institute, MUSSI |
| Item ID: | 14726 |
| Identification Number: | 10.1080/13658816.2019.1585541 |
| Depositing User: | Prof. Chris Brunsdon |
| Date Deposited: | 30 Aug 2021 14:23 |
| Journal or Publication Title: | International Journal of Geographical Information Science |
| Publisher: | Taylor & Francis |
| Refereed: | Yes |
| Related URLs: | |
| URI: | https://mu.eprints-hosting.org/id/eprint/14726 |
| Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
Repository Staff Only (login required)
- Item control page
Downloads
Downloads per month over past year
