GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION SEMIPARAMETRIC MODELING ON POVERTY PROBLEM
Regression analysis is a statistical method used to investigate and model the relationship between variables. Furthermore, a regression analysis was developed that involved spatial aspects, namely Geographically Weighted Regression (GWR). GWR modeling consists of various types, one of which is Geo...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Department of Statistics, Diponegoro University
2023
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/45756/1/Geographycally%20weighted%20panel%20logistic%20regression.pdf http://ir.unimas.my/id/eprint/45756/ https://ejournal.undip.ac.id/index.php/media_statistika/article/view/56717 https://doi.org/10.14710/medstat.16.1.47-58 |
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| Summary: | Regression analysis is a statistical method used to
investigate and model the relationship between variables.
Furthermore, a regression analysis was developed that involved spatial aspects, namely Geographically Weighted Regression (GWR). GWR modeling consists of various types, one of which is Geographically Weighted Logistic Regression
Semiparametric (GWLRS), an extension of the Logistic GWR
model that produces local and global parameter estimators. In this study, it is proposed to combine the GWLRS model using panel data or Geographically Weighted Panel Logistic
Regression Semiparametric (GWPLRS). The case study used in
this research is the problem of poverty in 38 regions/cities in East Java, Indonesia, in 2018 – 2022 as seen from the Poverty Gap Index. The weights used in this research are the adaptive gaussian kernel weighting functions. The results of the parameter significance test show that the Human Development Index as global variable has a significant effect on each region/city. |
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