Functional data analysis for extreme data

The performance of extreme data is observed by using functional data analysis with two extreme values theory approaches. Functional data analysis is one of the techniques to represent data in a functional form or as a smooth curve rather than in a discrete form. This functional observation will be f...

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Main Authors: Mohamad Adnan, Noor Izyan, Adam, Mohd. Bakri, Ishak, Mohd. Yusoff, Ibrahim, Noor Akma, Azmai, Mohammad Noor Amal
Format: Article
Language:English
Published: Indian Society for Education and Environment 2016
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/54357/
http://psasir.upm.edu.my/id/eprint/54357/1/Functional%20data%20analysis%20for%20extreme%20data.pdf
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author Mohamad Adnan, Noor Izyan
Adam, Mohd. Bakri
Ishak, Mohd. Yusoff
Ibrahim, Noor Akma
Azmai, Mohammad Noor Amal
author_facet Mohamad Adnan, Noor Izyan
Adam, Mohd. Bakri
Ishak, Mohd. Yusoff
Ibrahim, Noor Akma
Azmai, Mohammad Noor Amal
author_sort Mohamad Adnan, Noor Izyan
building UPM Institutional Repository
collection Online Access
description The performance of extreme data is observed by using functional data analysis with two extreme values theory approaches. Functional data analysis is one of the techniques to represent data in a functional form or as a smooth curve rather than in a discrete form. This functional observation will be fitted using fourier series by least squares and roughness penalty method. The data will be tested on block maxima and r-largest order statistics approaches to indicate what numbers of data required to have the best fitted curve. The finding illustrates three r-largest order statistics approach gives a better performance for functional data analysis which deals with extreme values data.
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institution Universiti Putra Malaysia
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language English
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publishDate 2016
publisher Indian Society for Education and Environment
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spelling upm-543572018-03-14T05:01:51Z http://psasir.upm.edu.my/id/eprint/54357/ Functional data analysis for extreme data Mohamad Adnan, Noor Izyan Adam, Mohd. Bakri Ishak, Mohd. Yusoff Ibrahim, Noor Akma Azmai, Mohammad Noor Amal The performance of extreme data is observed by using functional data analysis with two extreme values theory approaches. Functional data analysis is one of the techniques to represent data in a functional form or as a smooth curve rather than in a discrete form. This functional observation will be fitted using fourier series by least squares and roughness penalty method. The data will be tested on block maxima and r-largest order statistics approaches to indicate what numbers of data required to have the best fitted curve. The finding illustrates three r-largest order statistics approach gives a better performance for functional data analysis which deals with extreme values data. Indian Society for Education and Environment 2016-07 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/54357/1/Functional%20data%20analysis%20for%20extreme%20data.pdf Mohamad Adnan, Noor Izyan and Adam, Mohd. Bakri and Ishak, Mohd. Yusoff and Ibrahim, Noor Akma and Azmai, Mohammad Noor Amal (2016) Functional data analysis for extreme data. Indian Journal of Science and Technology, 9 (28). pp. 1-6. ISSN 0974-6846; ESSN: 0974-5645 http://www.indjst.org/index.php/indjst/article/view/97356 Functional data analysis; Extreme values theory; Fourier series; Generalize cross-validation 10.17485/ijst/2016/v9i28/97356
spellingShingle Functional data analysis; Extreme values theory; Fourier series; Generalize cross-validation
Mohamad Adnan, Noor Izyan
Adam, Mohd. Bakri
Ishak, Mohd. Yusoff
Ibrahim, Noor Akma
Azmai, Mohammad Noor Amal
Functional data analysis for extreme data
title Functional data analysis for extreme data
title_full Functional data analysis for extreme data
title_fullStr Functional data analysis for extreme data
title_full_unstemmed Functional data analysis for extreme data
title_short Functional data analysis for extreme data
title_sort functional data analysis for extreme data
topic Functional data analysis; Extreme values theory; Fourier series; Generalize cross-validation
url http://psasir.upm.edu.my/id/eprint/54357/
http://psasir.upm.edu.my/id/eprint/54357/
http://psasir.upm.edu.my/id/eprint/54357/
http://psasir.upm.edu.my/id/eprint/54357/1/Functional%20data%20analysis%20for%20extreme%20data.pdf