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...

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Autores principales:	Oluyemi A. Okunlola, Mohannad Alobid, Olusanya E. Olubusoye, Kayode Ayinde, Adewale F. Lukman, István Szűcs
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/89c3a63ca7a04b74a86c9cd1c33f18e1
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id	oai:doaj.org-article:89c3a63ca7a04b74a86c9cd1c33f18e1
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spelling	oai:doaj.org-article:89c3a63ca7a04b74a86c9cd1c33f18e12021-12-02T16:46:35ZSpatial regression and geostatistics discourse with empirical application to precipitation data in Nigeria10.1038/s41598-021-96124-x2045-2322https://doaj.org/article/89c3a63ca7a04b74a86c9cd1c33f18e12021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-96124-xhttps://doaj.org/toc/2045-2322Abstract 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.Oluyemi A. OkunlolaMohannad AlobidOlusanya E. OlubusoyeKayode AyindeAdewale F. LukmanIstván SzűcsNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q 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
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.
format	article
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
title	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_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_sort	spatial regression and geostatistics discourse with empirical application to precipitation data in nigeria
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/89c3a63ca7a04b74a86c9cd1c33f18e1
work_keys_str_mv	AT oluyemiaokunlola spatialregressionandgeostatisticsdiscoursewithempiricalapplicationtoprecipitationdatainnigeria AT mohannadalobid spatialregressionandgeostatisticsdiscoursewithempiricalapplicationtoprecipitationdatainnigeria AT olusanyaeolubusoye spatialregressionandgeostatisticsdiscoursewithempiricalapplicationtoprecipitationdatainnigeria AT kayodeayinde spatialregressionandgeostatisticsdiscoursewithempiricalapplicationtoprecipitationdatainnigeria AT adewaleflukman spatialregressionandgeostatisticsdiscoursewithempiricalapplicationtoprecipitationdatainnigeria AT istvanszucs spatialregressionandgeostatisticsdiscoursewithempiricalapplicationtoprecipitationdatainnigeria
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Spatial regression and geostatistics discourse with empirical application to precipitation data in Nigeria

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