REGRESI TERBOBOT GEOGRAFIS CAMPURAN MENGGUNAKAN KERNEL GAUSSIAN; MIXED GEOGRAPHICALLY WEIGHTED REGRESSION USING GAUSSIAN KERNEL

Sri Damayanti, Sri Haryatmi

2014 | Disertasi | PROGRAM STUDI S2 MATEMATIKA

Mixed Geographically Weighted Regression (MGWR) model is combination between linear regression model and Geographically Weighted Regression (GWR) model, which result is an estimation estimates having the quality of global and another parameter is local based on observation location. In the tesis studied Mixed Geographically Weighted Regression (MGWR) model using gaussian kernel function applied in the case population density at Tidore island. The analysis results Geographically Weighted Regression model using gaussian kernel is the best model. Based on the results significant variable tests MGWR formed 31 model and devided into 11 groups. The household electricity users (X9) that is variable affect global, each another variables variation in villages

Kata Kunci : GWR, MGWR, gaussian kernel, population density