Functional extreme data analysis methods and its application to rainfall data

Functional data analysis is one of the new techniques to transform a discrete or continuous observation into a functional form. Conventional classical statistics methods now can be observed and analyzed through a curve for almost all types of data with neither distribution assumption nor goodn...

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Bibliographic Details
Main Author:	Mohamad Adnan, Noor Izyan
Format:	Thesis
Language:	English
Published:	2018
Subjects:	Multivariate analysis - Case studies Mathematical statistics Rain and rainfall
Online Access:	http://psasir.upm.edu.my/id/eprint/77182/1/IPM%202018%2011%20IR.pdf
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id	my-upm-ir.77182
record_format	uketd_dc
spelling	my-upm-ir.771822024-04-02T00:21:16Z Functional extreme data analysis methods and its application to rainfall data 2018-01 Mohamad Adnan, Noor Izyan Functional data analysis is one of the new techniques to transform a discrete or continuous observation into a functional form. Conventional classical statistics methods now can be observed and analyzed through a curve for almost all types of data with neither distribution assumption nor goodness of fit test that are necessary to be followed. Literature reviews show that there is no study found for functional data analysis application on extreme data which deals with maximum value in the data set. In this thesis, the study has extended the functional data analysis methodology to cover on extreme data with several substitution methods have been introduced. Some characteristics of functional extreme data analysis such as on environmental data are explained. The tolerance bands for functional mean extreme data is proposed using bootstrapping method by implementing the percentile computation in determining the upper and lower limits of the mean function. The performance of the functional extreme data analysis is carried out. The equal and unequal space of time cases are considered to be implemented for the functional extreme data. The study found that only data that consists a large number of extreme data will be performed in functional extreme data for unequal space of time. Otherwise, a small number of extreme data is suggested to use the equal space of time to obtain a smooth curve. Multivariate analysis - Case studies Mathematical statistics Rain and rainfall 2018-01 Thesis http://psasir.upm.edu.my/id/eprint/77182/ http://psasir.upm.edu.my/id/eprint/77182/1/IPM%202018%2011%20IR.pdf text en public doctoral Universiti Putra Malaysia Multivariate analysis - Case studies Mathematical statistics Rain and rainfall Adam, Mohd Bakri
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
advisor	Adam, Mohd Bakri
topic	Multivariate analysis - Case studies Mathematical statistics Rain and rainfall
spellingShingle	Multivariate analysis - Case studies Mathematical statistics Rain and rainfall Mohamad Adnan, Noor Izyan Functional extreme data analysis methods and its application to rainfall data
description	Functional data analysis is one of the new techniques to transform a discrete or continuous observation into a functional form. Conventional classical statistics methods now can be observed and analyzed through a curve for almost all types of data with neither distribution assumption nor goodness of fit test that are necessary to be followed. Literature reviews show that there is no study found for functional data analysis application on extreme data which deals with maximum value in the data set. In this thesis, the study has extended the functional data analysis methodology to cover on extreme data with several substitution methods have been introduced. Some characteristics of functional extreme data analysis such as on environmental data are explained. The tolerance bands for functional mean extreme data is proposed using bootstrapping method by implementing the percentile computation in determining the upper and lower limits of the mean function. The performance of the functional extreme data analysis is carried out. The equal and unequal space of time cases are considered to be implemented for the functional extreme data. The study found that only data that consists a large number of extreme data will be performed in functional extreme data for unequal space of time. Otherwise, a small number of extreme data is suggested to use the equal space of time to obtain a smooth curve.
format	Thesis
qualification_level	Doctorate
author	Mohamad Adnan, Noor Izyan
author_facet	Mohamad Adnan, Noor Izyan
author_sort	Mohamad Adnan, Noor Izyan
title	Functional extreme data analysis methods and its application to rainfall data
title_short	Functional extreme data analysis methods and its application to rainfall data
title_full	Functional extreme data analysis methods and its application to rainfall data
title_fullStr	Functional extreme data analysis methods and its application to rainfall data
title_full_unstemmed	Functional extreme data analysis methods and its application to rainfall data
title_sort	functional extreme data analysis methods and its application to rainfall data
granting_institution	Universiti Putra Malaysia
publishDate	2018
url	http://psasir.upm.edu.my/id/eprint/77182/1/IPM%202018%2011%20IR.pdf
_version_	1804888723857342464

Functional extreme data analysis methods and its application to rainfall data

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