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.
Select the geometry column to use.
The column containing the dependent variable to use for the calculation of Multiscale Geographically Weighted Regression.
The columns containing the independent variables to use for the calculation of Multiscale Geographically Weighted Regression.
Bw search method: ‘golden’, ‘interval’. Golden Search— Determines either the number of neighbors or distance band for each explanatory variable using the Golden Search algorithm. This method searches multiple combinations of values for each explanatory variable between a specified minimum and maximum value. Intervals— Determines the number of neighbors or distance band for each explanatory variable by incrementing the number of neighbors or distance band from a minimum value.
Min value used in bandwidth search
type of kernel function used to weight observations; available options: ‘gaussian’ ‘bisquare’ ‘exponential’
Select the geometry column to use.
The column contains the dependent variable to use for the calculation of Multiscale Geographically Weighted Regression.
The columns containing the independent variables to use for the calculation of Multiscale Geographically Weighted Regression.
True for distance-based kernel function and False for adaptive (nearest neighbor) kernel function (default).
Type of kernel function used to weight observations; available options: ‘gaussian’, ‘bisquare’, ‘exponential’.
Bw search method: ‘golden’, ‘interval’. Golden Search— Determines either the number of neighbors or distance band for each explanatory variable using the Golden Search algorithm. This method searches multiple combinations of values for each explanatory variable between a specified minimum and maximum value. Intervals— Determines the number of neighbors or distance band for each explanatory variable by incrementing the number of neighbors or distance band from a minimum value.
Min value used in bandwidth search.
Max value used in bandwidth search.
Interval used in bandwidth search.
Criterion used in bandwidth search: ‘AICc’, ‘AIC’, ‘BIC’, ‘CV’.
Advanced Setting
specify form of corrected denominator of sigma squared to use for model diagnostics; Acceptable options are: ‘True’: n-tr(S) (default) ‘False’: n-2(tr(S)+tr(S’S))
True to include intercept (default) in model and False to exclude intercept.
True for spherical coordinates (long-lat), False for projected coordinates (default).
True to store full n by n hat matrix, False to not store full hat matrix to minimize memory footprint (default).
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