REGRESI TERBOBOT GEOGRAFIS CAMPURAN MENGGUNAKAN KERNEL GAUSSIAN
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 stu...
محفوظ في:
| المؤلفون الرئيسيون: | , |
|---|---|
| التنسيق: | Theses and Dissertations NonPeerReviewed |
| منشور في: |
[Yogyakarta] : Universitas Gadjah Mada
2014
|
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://repository.ugm.ac.id/134057/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=75032 |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
| الملخص: | 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 |
|---|