Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices

@article{Huang2010GeographicallyAT,
  title={Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices},
  author={Bo Huang and Bo Wu and Michael Barry},
  journal={International Journal of Geographical Information Science},
  year={2010},
  volume={24},
  pages={383-401}
}
By incorporating temporal effects into the geographically weighted regression (GWR) model, an extended GWR model, geographically and temporally weighted regression (GTWR), has been developed to deal with both spatial and temporal nonstationarity simultaneously in real estate market data. Unlike the standard GWR model, GTWR integrates both temporal and spatial information in the weighting matrices to capture spatial and temporal heterogeneity. The GTWR design embodies a local weighting scheme… CONTINUE READING
Highly Cited
This paper has 71 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 41 extracted citations

71 Citations

01020'10'12'14'16'18
Citations per Year
Semantic Scholar estimates that this publication has 71 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 27 references

Thematic map comparison: evaluating the statistical significance of differences in classification accuracy

  • G. M. Foody
  • Photogrammetric Engineering and Remote Sensing,
  • 2004
Highly Influential
3 Excerpts

Spatio-temporal analysis of rural-urban land conversion

  • B. Huang, L. Zhang, B. Wu
  • International Journal of Geographical Information…
  • 2009
1 Excerpt

Exploring spatial effects on housing price: the case study of the city of Calgary

  • P. Wang
  • 2006
1 Excerpt

Similar Papers

Loading similar papers…