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 Geogr...
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| Format: | Article |
| Language: | English |
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Universitas Diponegoro
2023-11-01
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| Series: | Media Statistika |
| Subjects: | |
| Online Access: | https://ejournal.undip.ac.id/index.php/media_statistika/article/view/56717 |
| _version_ | 1797394893649215488 |
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| author | Aliyah Husnun Azizah Nurjannah Nurjannah Adji Achmad Rinaldo Fernandes Rosita Hamdan |
| author_facet | Aliyah Husnun Azizah Nurjannah Nurjannah Adji Achmad Rinaldo Fernandes Rosita Hamdan |
| author_sort | Aliyah Husnun Azizah |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T00:26:22Z |
| format | Article |
| id | doaj.art-7a42d1a276584475bd63f8a6834cf07f |
| institution | Directory Open Access Journal |
| issn | 1979-3693 2477-0647 |
| language | English |
| last_indexed | 2024-03-09T00:26:22Z |
| publishDate | 2023-11-01 |
| publisher | Universitas Diponegoro |
| record_format | Article |
| series | Media Statistika |
| spelling | doaj.art-7a42d1a276584475bd63f8a6834cf07f2023-12-12T02:27:51ZengUniversitas DiponegoroMedia Statistika1979-36932477-06472023-11-01161475810.14710/medstat.16.1.47-5822920GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION SEMIPARAMETRIC MODELING ON POVERTY PROBLEMAliyah Husnun Azizah0Nurjannah Nurjannah1Adji Achmad Rinaldo Fernandes2Rosita Hamdan3Department of Statistics, Faculty of Mathematics and Natural Sciences, Brawijaya University, IndonesiaDepartment of Statistics, Faculty of Mathematics and Natural Sciences, Brawijaya University, IndonesiaDepartment of Statistics, Faculty of Mathematics and Natural Sciences, Brawijaya University, IndonesiaDepartment of Development Economics, University Malaysia Serawak, MalaysiaRegression 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.https://ejournal.undip.ac.id/index.php/media_statistika/article/view/56717geographically weighted regressiongeographically weighted panel logistic regression semiparametricpoverty gap index. |
| spellingShingle | Aliyah Husnun Azizah Nurjannah Nurjannah Adji Achmad Rinaldo Fernandes Rosita Hamdan GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION SEMIPARAMETRIC MODELING ON POVERTY PROBLEM Media Statistika geographically weighted regression geographically weighted panel logistic regression semiparametric poverty gap index. |
| title | 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_short | GEOGRAPHICALLY WEIGHTED PANEL LOGISTIC REGRESSION SEMIPARAMETRIC MODELING ON POVERTY PROBLEM |
| title_sort | geographically weighted panel logistic regression semiparametric modeling on poverty problem |
| topic | geographically weighted regression geographically weighted panel logistic regression semiparametric poverty gap index. |
| url | https://ejournal.undip.ac.id/index.php/media_statistika/article/view/56717 |
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