Selection of optimal knot point and best geographic weighted on geographically weighted spline nonparametric regression model.

This study proposes the development of a nonparametric regression model combined with geographically weighted regression. The regression model considers geographical factors and has a data pattern that does not follow a parametric form to overcome the problem of spatial heterogeneity and unknown regression functions. This study aims to model provincial food security index data in Indonesia with the GWSNR model, so finding the optimal knot point and the best geographic weighting is necessary.

Determination of the best geographic weighted function and estimation of spatio temporal model - Geographically weighted panel regression using weighted least square.

This study proposes the development of a spatio-temporal model with geographic weights containing elements of location, time and the correlation between the two. The spatio-temporal model is a spatial regression model that combines geographic information and time series simultaneously. The model can overcome the problem of spatial heterogeneity and spatial effects.