Spatial regression and geostatistics discourse with empirical application to precipitation data in Nigeria
Abstract In this study, we propose a robust approach to handling geo-referenced data and discuss its statistical analysis. The linear regression model has been found inappropriate in this type of study. This motivates us to redefine its error structure to incorporate the spatial components inherent...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-96124-x |
| _version_ | 1819194845076389888 |
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| author | Oluyemi A. Okunlola Mohannad Alobid Olusanya E. Olubusoye Kayode Ayinde Adewale F. Lukman István Szűcs |
| author_facet | Oluyemi A. Okunlola Mohannad Alobid Olusanya E. Olubusoye Kayode Ayinde Adewale F. Lukman István Szűcs |
| author_sort | Oluyemi A. Okunlola |
| collection | DOAJ |
| description | Abstract In this study, we propose a robust approach to handling geo-referenced data and discuss its statistical analysis. The linear regression model has been found inappropriate in this type of study. This motivates us to redefine its error structure to incorporate the spatial components inherent in the data into the model. Therefore, four spatial models emanated from the re-definition of the error structure. We fitted the spatial and the non-spatial linear model to the precipitation data and compared their results. All the spatial models outperformed the non-spatial model. The Spatial Autoregressive with additional autoregressive error structure (SARAR) model is the most adequate among the spatial models. Furthermore, we identified the hot and cold spot locations of precipitation and their spatial distribution in the study area. |
| first_indexed | 2024-12-23T02:03:20Z |
| format | Article |
| id | doaj.art-89c3a63ca7a04b74a86c9cd1c33f18e1 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-23T02:03:20Z |
| publishDate | 2021-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-89c3a63ca7a04b74a86c9cd1c33f18e12022-12-21T18:03:56ZengNature PortfolioScientific Reports2045-23222021-08-0111111410.1038/s41598-021-96124-xSpatial regression and geostatistics discourse with empirical application to precipitation data in NigeriaOluyemi A. Okunlola0Mohannad Alobid1Olusanya E. Olubusoye2Kayode Ayinde3Adewale F. Lukman4István Szűcs5Department of Mathematical and Computer Sciences, University of Medical SciencesFaculty of Economics and Business, Institute of Applied Economic Sciences, University of DebrecenDepartment of Statistics, University of IbadanDepartment of Statistics, Federal University of TechnologyDepartment of Mathematical and Computer Sciences, University of Medical SciencesFaculty of Economics and Business, Institute of Applied Economic Sciences, University of DebrecenAbstract In this study, we propose a robust approach to handling geo-referenced data and discuss its statistical analysis. The linear regression model has been found inappropriate in this type of study. This motivates us to redefine its error structure to incorporate the spatial components inherent in the data into the model. Therefore, four spatial models emanated from the re-definition of the error structure. We fitted the spatial and the non-spatial linear model to the precipitation data and compared their results. All the spatial models outperformed the non-spatial model. The Spatial Autoregressive with additional autoregressive error structure (SARAR) model is the most adequate among the spatial models. Furthermore, we identified the hot and cold spot locations of precipitation and their spatial distribution in the study area.https://doi.org/10.1038/s41598-021-96124-x |
| spellingShingle | Oluyemi A. Okunlola Mohannad Alobid Olusanya E. Olubusoye Kayode Ayinde Adewale F. Lukman István Szűcs Spatial regression and geostatistics discourse with empirical application to precipitation data in Nigeria Scientific Reports |
| title | Spatial regression and geostatistics discourse with empirical application to precipitation data in Nigeria |
| title_full | Spatial regression and geostatistics discourse with empirical application to precipitation data in Nigeria |
| title_fullStr | Spatial regression and geostatistics discourse with empirical application to precipitation data in Nigeria |
| title_full_unstemmed | Spatial regression and geostatistics discourse with empirical application to precipitation data in Nigeria |
| title_short | Spatial regression and geostatistics discourse with empirical application to precipitation data in Nigeria |
| title_sort | spatial regression and geostatistics discourse with empirical application to precipitation data in nigeria |
| url | https://doi.org/10.1038/s41598-021-96124-x |
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