Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 28, Pages: 1-6
Noor Izyan Mohamad Adnan1 *, Mohd. Bakri Adam1 , Mohd. Yusoff Ishak2 , Noor Akma Ibrahim3 and Mohammad Noor Amal Azmai4
1 Institute for Mathematical Research, [email protected]
2 Faculty of Environmental Studies,
3 Mathematical Department, Faculty of Science,
4 Depatment of Biology, Faculty of Science,
*Author for correspondence
Noor Izyan Mohamad Adnan
Institute for Mathematical Research,
Email: [email protected]
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.
Keywords: Functional Data Analysis, Extreme Values Theory, Fourier Series, Generalize Cross-validation
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