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Functional data analysis for extreme data


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


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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Additional Metadata

Item Type: Article
Subject: Functional data analysis; Extreme values theory; Fourier series; Generalize cross-validation
Divisions: Faculty of Environmental Studies
Faculty of Science
Institute for Mathematical Research
DOI Number: https://doi.org/10.17485/ijst/2016/v9i28/97356
Publisher: Indian Society for Education and Environment
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 14 Mar 2018 05:01
Last Modified: 14 Mar 2018 05:01
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.17485/ijst/2016/v9i28/97356
URI: http://psasir.upm.edu.my/id/eprint/54357
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