A Comparison of Bandwidth and Kernel Function Selection in Geographically Weighted Regression for House Valuation-Reference-Cited by-同舟云学术

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A Comparison of Bandwidth and Kernel Function Selection in Geographically Weighted Regression for House Valuation

Published:2019-01-25 Issue:1 Volume:10 Page:58
ISSN:2087-2100
Container-title:International Journal of Technology
language:
Short-container-title:IJTech

Author:

Yacim Joseph Awoamim,Boshoff Douw Gert Brand

Publisher

International Journal of Technology

Subject

Management of Technology and Innovation,Strategy and Management,General Engineering

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Exploring zonal heterogeneities of primary school students’ commute-mode choices through a geographically weighted regression model;Journal of Geographical Sciences;2024-04

2. Exploring Multiscale Spatial Interactions: Multiscale Geographically Weighted Negative Binomial Regression;Annals of the American Association of Geographers;2024-02-06

3. Comparison of spatial autoregressive (SAR) and geographically weighted regression (GWR) based on simulation study;AIP Conference Proceedings;2024

4. Prediction Land Value Using Geographically Weighted Extreme Learning Machine;2023 7th International Conference on New Media Studies (CONMEDIA);2023-12-06

5. A Survey of Methods and Input Data Types for House Price Prediction;ISPRS International Journal of Geo-Information;2023-05-14

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