APPLICATION OF PENALIZED SPLINE-SPATIAL AUTOREGRESSIVE MODEL TO HIV CASE DATA IN INDONESIA
Spatial regression analysis is a statistical method used to perform modeling by considering spatial effects. Spatial models generally use a parametric approach by assuming a linear relationship between explanatory and response variables. The nonparametric regression method is better suited for data...
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Universitas Pattimura
2023-04-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7683 |
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| author | Nindi Pigitha Anik Djuraidah Aji Hamim Wigena |
| author_facet | Nindi Pigitha Anik Djuraidah Aji Hamim Wigena |
| author_sort | Nindi Pigitha |
| collection | DOAJ |
| description | Spatial regression analysis is a statistical method used to perform modeling by considering spatial effects. Spatial models generally use a parametric approach by assuming a linear relationship between explanatory and response variables. The nonparametric regression method is better suited for data with a nonlinear connection because it does not need linear assumptions. One of the nonparametric regression methods is penalized spline regression (P-Spline). The P-spline has a simple mathematical relationship with mixed linear model. The use of a mixed linear model allows the P-Spline to be combined with other statistical models. PS-SAR is a combination of the P-Spline and the SAR spatial model so that it can analyze spatial data with a semiparametric approach. Based on data from monitoring the development of the HIV situation in 2018, the number of HIV cases in Indonesia shows a clustered pattern that indicate spatial dependence. In addition, the relationship between the number of positive cases and the factors tends to be nonlinear. Therefore, this study aims to apply the PS-SAR model to HIV case data in Indonesia. The resulting model is evaluated based on the estimates of autoregressive spatial coefficient, MSE, MAPE, and Pseudo R2. Based on the results, the PS-SAR model has an autoregressive spatial coefficient similar to the SAR model and has smaller MSE and MAPE than the SAR model. |
| format | Article |
| id | doaj-art-b1e0a8d91cbb418bb8d4f10c8dc7c8c0 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2023-04-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-b1e0a8d91cbb418bb8d4f10c8dc7c8c02025-08-20T03:35:56ZengUniversitas PattimuraBarekeng1978-72272615-30172023-04-011710527053410.30598/barekengvol17iss1pp0527-05347683APPLICATION OF PENALIZED SPLINE-SPATIAL AUTOREGRESSIVE MODEL TO HIV CASE DATA IN INDONESIANindi Pigitha0Anik Djuraidah1Aji Hamim Wigena2Department of Statistics, Faculty Mathematics and Natural Sciences, IPB University, IndonesiaDepartment of Statistics, Faculty Mathematics and Natural Sciences, IPB University, IndonesiaDepartment of Statistics, Faculty Mathematics and Natural Sciences, IPB University, IndonesiaSpatial regression analysis is a statistical method used to perform modeling by considering spatial effects. Spatial models generally use a parametric approach by assuming a linear relationship between explanatory and response variables. The nonparametric regression method is better suited for data with a nonlinear connection because it does not need linear assumptions. One of the nonparametric regression methods is penalized spline regression (P-Spline). The P-spline has a simple mathematical relationship with mixed linear model. The use of a mixed linear model allows the P-Spline to be combined with other statistical models. PS-SAR is a combination of the P-Spline and the SAR spatial model so that it can analyze spatial data with a semiparametric approach. Based on data from monitoring the development of the HIV situation in 2018, the number of HIV cases in Indonesia shows a clustered pattern that indicate spatial dependence. In addition, the relationship between the number of positive cases and the factors tends to be nonlinear. Therefore, this study aims to apply the PS-SAR model to HIV case data in Indonesia. The resulting model is evaluated based on the estimates of autoregressive spatial coefficient, MSE, MAPE, and Pseudo R2. Based on the results, the PS-SAR model has an autoregressive spatial coefficient similar to the SAR model and has smaller MSE and MAPE than the SAR model.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7683human immunodeficiency virusnonlinearspatial autoregressive modelsemiparametricspenalized splinepenalized spline-spatial autoregressive model |
| spellingShingle | Nindi Pigitha Anik Djuraidah Aji Hamim Wigena APPLICATION OF PENALIZED SPLINE-SPATIAL AUTOREGRESSIVE MODEL TO HIV CASE DATA IN INDONESIA Barekeng human immunodeficiency virus nonlinear spatial autoregressive model semiparametrics penalized spline penalized spline-spatial autoregressive model |
| title | APPLICATION OF PENALIZED SPLINE-SPATIAL AUTOREGRESSIVE MODEL TO HIV CASE DATA IN INDONESIA |
| title_full | APPLICATION OF PENALIZED SPLINE-SPATIAL AUTOREGRESSIVE MODEL TO HIV CASE DATA IN INDONESIA |
| title_fullStr | APPLICATION OF PENALIZED SPLINE-SPATIAL AUTOREGRESSIVE MODEL TO HIV CASE DATA IN INDONESIA |
| title_full_unstemmed | APPLICATION OF PENALIZED SPLINE-SPATIAL AUTOREGRESSIVE MODEL TO HIV CASE DATA IN INDONESIA |
| title_short | APPLICATION OF PENALIZED SPLINE-SPATIAL AUTOREGRESSIVE MODEL TO HIV CASE DATA IN INDONESIA |
| title_sort | application of penalized spline spatial autoregressive model to hiv case data in indonesia |
| topic | human immunodeficiency virus nonlinear spatial autoregressive model semiparametrics penalized spline penalized spline-spatial autoregressive model |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7683 |
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