Open AccessPemodelan Semiparametrik Geographical Weighted Logistic Regression pada Data Kemiskinan di Provinsi Sulawesi Selatan Tahun 2017
Author(s) -
Fitriatusakiah Fitriatusakiah,
Andi Kresna Jaya,
La Podje Talangko
Publication year - 2021
Publication title -
estimasi
Language(s) - English
Resource type - Journals
eISSN - 2721-3803
pISSN - 2721-379X
DOI - 10.20956/ejsa.v2i2.11309
Subject(s) - estimator , logistic regression , semiparametric model , econometrics , statistics , semiparametric regression , poverty , mathematics , estimation , geography , economics , economic growth , management
The level of poverty in a Regency/city in South Sulawesi in 2017 is different. The grouping of poverty status can be done based on the value of the HeadCount Index (HCI) of South Sulawesi. Factors affecting poverty will differ for each area being observed. The statistical modeling method developed for data analysis by taking into account the location factor is semiparametric Geographical Weighted Logistic Regression (GWLR). The GWLR semiparametric Model consists of parameters that are affected by the location and not affected by the location. The parameter estimator of the GWLR semiparametric model used in this research was obtained using the maximum method likelihood estimation. The result of a semiparametric model of GWLR each district/city in South Sulawesi in 2017 has the value Estimator parameter for global parameters is the same value for each location, namely, a3 = 0.1724, a4 = 0.0204, and a6 = 0.0261 whereas the parameter estimator for local parameters has different values so that GWLR semiparametric model of each district/city.