Indonesian Journal of Statistics and Its Applications
Vol 3 No 3 (2019)

THE BEST GLOBAL AND LOCAL VARIABLES OF THE MIXED GEOGRAPHICALLY AND TEMPORALLY WEIGHTED REGRESSION MODEL

Nuramaliyah Nuramaliyah (Department of Statistics, IPB University, Indonesia)
Asep Saefuddin (Department of Statistics, IPB University, Indonesia)
Muhammad Nur Aidi (Department of Statistics, IPB University, Indonesia)



Article Info

Publish Date
31 Oct 2019

Abstract

Geographically and temporally weighted regression (GTWR) is a method used when there is spatial and temporal diversity in an observation. GTWR model just consider the local influences of spatial-temporal independent variables on dependent variable. In some cases, the model not only about local influences but there are the global influences of spatial-temporal variables too, so that mixed geographically and temporally weighted regression (MGTWR) model more suitable to use. This study aimed to determine the best global and local variables in MGTWR and to determine the model to be used in North Sumatra’s poverty cases in 2010 to 2015. The result show that the Unemployment rate and labor force participation rates are global variables. Whereas the variable literacy rate, school enrollment rates and households buying rice for poor (raskin) are local variables. Furthermore, Based on Root Mean Square Error (RMSE) and Akaike Information Criterion (AIC) showed that MGTWR better than GTWR when it used in North Sumatra’s poverty cases.

Copyrights © 2019






Journal Info

Abbrev

ijsa

Publisher

Subject

Computer Science & IT Mathematics Other

Description

Indonesian Journal of Statistics and Its Applications (eISSN:2599-0802) (formerly named Forum Statistika dan Komputasi), established since 2017, publishes scientific papers in the area of statistical science and the applications. The published papers should be research papers with, but not limited ...