%0 Journal Article %1 journals/gis/LiFLO19 %A Li, Ziqi %A Fotheringham, A. Stewart %A Li, Wenwen %A Oshan, Taylor %D 2019 %J Int. J. Geogr. Inf. Sci. %K dblp %N 1 %P 155-175 %T Fast Geographically Weighted Regression (FastGWR): a scalable algorithm to investigate spatial process heterogeneity in millions of observations. %U http://dblp.uni-trier.de/db/journals/gis/gis33.html#LiFLO19 %V 33

@article{journals/gis/LiFLO19, added-at = {2020-05-12T00:00:00.000+0200}, author = {Li, Ziqi and Fotheringham, A. Stewart and Li, Wenwen and Oshan, Taylor}, biburl = {https://www.bibsonomy.org/bibtex/2a5a1dfe0aedac54380120894275e515b/dblp}, ee = {https://doi.org/10.1080/13658816.2018.1521523}, interhash = {82db60ac6d453b12e5c0689060ea85a8}, intrahash = {a5a1dfe0aedac54380120894275e515b}, journal = {Int. J. Geogr. Inf. Sci.}, keywords = {dblp}, number = 1, pages = {155-175}, timestamp = {2020-05-13T12:00:51.000+0200}, title = {Fast Geographically Weighted Regression (FastGWR): a scalable algorithm to investigate spatial process heterogeneity in millions of observations.}, url = {http://dblp.uni-trier.de/db/journals/gis/gis33.html#LiFLO19}, volume = 33, year = 2019 }