MGWR Model

Multiscale Geographically Weighted Regression estimation. More details can be found at 1. A. Stewart Fotheringham, Wenbai Yang, and Wei Kang. Multiscale geographically weighted regression (mgwr). Annals of the American Association of Geographers, 107(6):1247–1265, 2017. URL: http://dx.doi.org/10.1080/24694452.2017.1352480, arXiv:http://dx.doi.org/10.1080/24694452.2017.1352480, doi:10.1080/24694452.2017.1352480. and Hanchen Yu, Alexander Stewart Fotheringham, Ziqi Li, Taylor Oshan, Wei Kang, and Levi John Wolf. Inference in multiscale geographically weighted regression. Geographical Analysis, 2019. URL: https://onlinelibrary.wiley.com/doi/abs/10.1111/gean.12189, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1111/gean.12189, doi:10.1111/gean.12189. 2. https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-statistics/how-multiscale-geographically-weighted-regression-mgwr-works.htm

Note: The input table should not contain missing values. You can use the Missing Value node to replace them.

Input ports

1. Type: Table
   Input Table

   The input table containing the data to use for the calculation of Multiscale Geographically Weighted Regression.

Output ports

1. Type: Table
   Model Coefficients Table

   The output table containing the model coefficients for Multiscale Geographically Weighted Regression.