Modeling the Extreme Rainfall Data of Several Sites in Sabah using Sandwich Estimator

When the extreme data were obtained from several sites in a region, spatial extreme analysis is always been considered. In this paper, we model the annual maximum rainfall data by using generalized extreme value distribution. We fit the model independently for each site to prevent extreme value comp...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Siow Chen Sian, Darmesah Gabda
Formato:	article
Lenguaje:	EN
Publicado:	Tamkang University Press 2021
Materias:	generalized extreme value (gev) distribution penalized maximum likelihood estimation (pmle) sandwich estimator return level Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Physics QC1-999
Acceso en línea:	https://doaj.org/article/f30b5cc95dd34b78813c3a5309dd920c
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:f30b5cc95dd34b78813c3a5309dd920c
record_format	dspace
spelling	oai:doaj.org-article:f30b5cc95dd34b78813c3a5309dd920c2021-11-24T14:42:36ZModeling the Extreme Rainfall Data of Several Sites in Sabah using Sandwich Estimator10.6180/jase.202206_25(3).00072708-99672708-9975https://doaj.org/article/f30b5cc95dd34b78813c3a5309dd920c2021-11-01T00:00:00Zhttp://jase.tku.edu.tw/articles/jase-202206-25-3-0007https://doaj.org/toc/2708-9967https://doaj.org/toc/2708-9975When the extreme data were obtained from several sites in a region, spatial extreme analysis is always been considered. In this paper, we model the annual maximum rainfall data by using generalized extreme value distribution. We fit the model independently for each site to prevent extreme value complex modeling. However, it also causes the statistical assumption of dependency between sites to be violated. Therefore, we applied the sandwich estimator to correct the variance of the model. We also consider an analysis of small sample sizes of the observed data. The method of penalized maximum likelihood estimation was carried out to improve the inference of the model. In the end, the return levels of the annual maximum rainfall data were computed by using the corrected model. Siow Chen SianDarmesah GabdaTamkang University Pressarticlegeneralized extreme value (gev) distributionpenalized maximum likelihood estimation (pmle)sandwich estimatorreturn levelEngineering (General). Civil engineering (General)TA1-2040Chemical engineeringTP155-156PhysicsQC1-999ENJournal of Applied Science and Engineering, Vol 25, Iss 3, Pp 417-420 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	generalized extreme value (gev) distribution penalized maximum likelihood estimation (pmle) sandwich estimator return level Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Physics QC1-999
spellingShingle	generalized extreme value (gev) distribution penalized maximum likelihood estimation (pmle) sandwich estimator return level Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Physics QC1-999 Siow Chen Sian Darmesah Gabda Modeling the Extreme Rainfall Data of Several Sites in Sabah using Sandwich Estimator
description	When the extreme data were obtained from several sites in a region, spatial extreme analysis is always been considered. In this paper, we model the annual maximum rainfall data by using generalized extreme value distribution. We fit the model independently for each site to prevent extreme value complex modeling. However, it also causes the statistical assumption of dependency between sites to be violated. Therefore, we applied the sandwich estimator to correct the variance of the model. We also consider an analysis of small sample sizes of the observed data. The method of penalized maximum likelihood estimation was carried out to improve the inference of the model. In the end, the return levels of the annual maximum rainfall data were computed by using the corrected model.
format	article
author	Siow Chen Sian Darmesah Gabda
author_facet	Siow Chen Sian Darmesah Gabda
author_sort	Siow Chen Sian
title	Modeling the Extreme Rainfall Data of Several Sites in Sabah using Sandwich Estimator
title_short	Modeling the Extreme Rainfall Data of Several Sites in Sabah using Sandwich Estimator
title_full	Modeling the Extreme Rainfall Data of Several Sites in Sabah using Sandwich Estimator
title_fullStr	Modeling the Extreme Rainfall Data of Several Sites in Sabah using Sandwich Estimator
title_full_unstemmed	Modeling the Extreme Rainfall Data of Several Sites in Sabah using Sandwich Estimator
title_sort	modeling the extreme rainfall data of several sites in sabah using sandwich estimator
publisher	Tamkang University Press
publishDate	2021
url	https://doaj.org/article/f30b5cc95dd34b78813c3a5309dd920c
work_keys_str_mv	AT siowchensian modelingtheextremerainfalldataofseveralsitesinsabahusingsandwichestimator AT darmesahgabda modelingtheextremerainfalldataofseveralsitesinsabahusingsandwichestimator
_version_	1718415023893643264

Modeling the Extreme Rainfall Data of Several Sites in Sabah using Sandwich Estimator

Ejemplares similares