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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Department of Statistics, Diponegoro University
2023
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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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my.unimas.ir.457562024-08-22T05:37:36Z http://ir.unimas.my/id/eprint/45756/ GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION SEMIPARAMETRIC MODELING ON POVERTY PROBLEM Aliyah Husnun, Azizah Adji Achmad Rinaldo, Fernandes Rosita, Hamdan HA Statistics HB Economic Theory 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. Department of Statistics, Diponegoro University 2023-09-20 Article PeerReviewed text en http://ir.unimas.my/id/eprint/45756/1/Geographycally%20weighted%20panel%20logistic%20regression.pdf Aliyah Husnun, Azizah and Adji Achmad Rinaldo, Fernandes and Rosita, Hamdan (2023) GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION SEMIPARAMETRIC MODELING ON POVERTY PROBLEM. MEDIA STATISTIKA, 16 (1). pp. 47-58. ISSN 1979 – 3693 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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HA Statistics HB Economic Theory Aliyah Husnun, Azizah Adji Achmad Rinaldo, Fernandes Rosita, Hamdan GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION SEMIPARAMETRIC MODELING ON POVERTY PROBLEM |
description |
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. |
format |
Article |
author |
Aliyah Husnun, Azizah Adji Achmad Rinaldo, Fernandes Rosita, Hamdan |
author_facet |
Aliyah Husnun, Azizah Adji Achmad Rinaldo, Fernandes Rosita, Hamdan |
author_sort |
Aliyah Husnun, Azizah |
title |
GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION
SEMIPARAMETRIC MODELING ON POVERTY PROBLEM |
title_short |
GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION
SEMIPARAMETRIC MODELING ON POVERTY PROBLEM |
title_full |
GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION
SEMIPARAMETRIC MODELING ON POVERTY PROBLEM |
title_fullStr |
GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION
SEMIPARAMETRIC MODELING ON POVERTY PROBLEM |
title_full_unstemmed |
GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION
SEMIPARAMETRIC MODELING ON POVERTY PROBLEM |
title_sort |
geographically weighted panel logistic regression
semiparametric modeling on poverty problem |
publisher |
Department of Statistics, Diponegoro University |
publishDate |
2023 |
url |
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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1808981515929911296 |
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13.19449 |