Thank you all for the input.
• My model predicts the price of a condominium apartment based on its characteristics. The independent variables include the floor level, the number of apartments on the floor, and the number of apartments in the building, among others.
• I’m not certain when the number of coincident features would pose a problem. Ultimately, the Geographically Weighted Regression (GWR) will assign weights to them according to the Gaussian equation. Their distance from the prediction point is zero, so their weight is 1.
• The Ordinary Least Squares (OLS) method works well without any issues. The results are shown in the screenshots below.
How to deal with the many errors generated by the GWR?
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Jamal Numan
Geomolg Geoportal for Spatial Information
Ramallah, West Bank, Palestine