Robust spatial temporal analysis with improved geographically and temporally weighted regression model of dengue incidence rate

Abstract

Improved Geographically and Temporally Weighted Regression (IGTWR) is a development of Geographically Weighted Regression (GWR) which involves elements of time and spatial-temporal interactions to see the effect of distance measured in spatial dimensions on temporal distance in modeling formation. This method produces a local model at each location, time, and also considers interactions in the dimensions of space and time so that the resulting model is more representative and compatible. IGTWR model parameters estimated using the WLS method are not robust to outliers. This can result in biased regression models and errors in concluding relationships between variables. Robust regression modeling with the M estimator developed in the IGTWR model and applied to the incidence of dengue hemorrhagic fever in South Sulawesi Province from 2016 to 2021 can overcome the outlier problem that occurred at the location and time studied. This is indicated by the predicted value of the RIGTWR model being closer to the actual value than the IGTWR model, a decrease in the RMSE and MAD values, and an increase in the Adjusted R Square value.