Bayesian extreme modeling for non-stationary air quality data
The aim of this paper is to model the non-stationary Generalized Extreme Value distribution with a focus on Bayesian approach. The location parameter is expressed in terms of linear trend over the time period while constant for both scale and shape parameters. This study also explores the informativ...
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
AIP Publishing LLC
2013
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/57200/ http://psasir.upm.edu.my/id/eprint/57200/1/Bayesian%20extreme%20modeling%20for%20non-stationary%20air%20quality%20data.pdf |
| _version_ | 1848853298763792384 |
|---|---|
| author | Mohd Amin, Nor Azrita Adam, Mohd Bakri Ibrahim, Noor Akma Aris, Ahmad Zaharin |
| author_facet | Mohd Amin, Nor Azrita Adam, Mohd Bakri Ibrahim, Noor Akma Aris, Ahmad Zaharin |
| author_sort | Mohd Amin, Nor Azrita |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The aim of this paper is to model the non-stationary Generalized Extreme Value distribution with a focus on Bayesian approach. The location parameter is expressed in terms of linear trend over the time period while constant for both scale and shape parameters. This study also explores the informative and Jeffrey's prior towards the efficiency of the estimating procedure. Root Mean Square Error is then use for choosing the best prior. Metropolis Hasting for extreme algorithm will also briefly explained in this study. The model is applied to the air quality data for Johor state. |
| first_indexed | 2025-11-15T10:51:45Z |
| format | Conference or Workshop Item |
| id | upm-57200 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T10:51:45Z |
| publishDate | 2013 |
| publisher | AIP Publishing LLC |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-572002017-09-08T10:29:48Z http://psasir.upm.edu.my/id/eprint/57200/ Bayesian extreme modeling for non-stationary air quality data Mohd Amin, Nor Azrita Adam, Mohd Bakri Ibrahim, Noor Akma Aris, Ahmad Zaharin The aim of this paper is to model the non-stationary Generalized Extreme Value distribution with a focus on Bayesian approach. The location parameter is expressed in terms of linear trend over the time period while constant for both scale and shape parameters. This study also explores the informative and Jeffrey's prior towards the efficiency of the estimating procedure. Root Mean Square Error is then use for choosing the best prior. Metropolis Hasting for extreme algorithm will also briefly explained in this study. The model is applied to the air quality data for Johor state. AIP Publishing LLC 2013 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/57200/1/Bayesian%20extreme%20modeling%20for%20non-stationary%20air%20quality%20data.pdf Mohd Amin, Nor Azrita and Adam, Mohd Bakri and Ibrahim, Noor Akma and Aris, Ahmad Zaharin (2013) Bayesian extreme modeling for non-stationary air quality data. In: International Conference on Mathematical Sciences and Statistics 2013 (ICMSS2013), 5-7 Feb. 2013, Kuala Lumpur, Malaysia. (pp. 424-428). 10.1063/1.4823949 |
| spellingShingle | Mohd Amin, Nor Azrita Adam, Mohd Bakri Ibrahim, Noor Akma Aris, Ahmad Zaharin Bayesian extreme modeling for non-stationary air quality data |
| title | Bayesian extreme modeling for non-stationary air quality data |
| title_full | Bayesian extreme modeling for non-stationary air quality data |
| title_fullStr | Bayesian extreme modeling for non-stationary air quality data |
| title_full_unstemmed | Bayesian extreme modeling for non-stationary air quality data |
| title_short | Bayesian extreme modeling for non-stationary air quality data |
| title_sort | bayesian extreme modeling for non-stationary air quality data |
| url | http://psasir.upm.edu.my/id/eprint/57200/ http://psasir.upm.edu.my/id/eprint/57200/ http://psasir.upm.edu.my/id/eprint/57200/1/Bayesian%20extreme%20modeling%20for%20non-stationary%20air%20quality%20data.pdf |