Statistical analysis of wind and rainfall with functional data analysis technique

The speed of wind and rainfall throughout Peninsular Malaysia varies from one region to another, depending on the direction of winds and rainfall that occur because of strong wind and the monsoons. Our data consist of daily mean wind and rainfall data from ten stations and covering 25 years period f...

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Main Author:	Wan Ismail, Wan Norliyana
Format:	Thesis
Language:	English
Published:	2014
Subjects:	QC Physics
Online Access:	http://eprints.utm.my/id/eprint/48621/1/WanNorliyanaWanIsmailMFS2014.pdf
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id	my-utm-ep.48621
record_format	uketd_dc
spelling	my-utm-ep.486212020-03-02T07:30:34Z Statistical analysis of wind and rainfall with functional data analysis technique 2014 Wan Ismail, Wan Norliyana QC Physics The speed of wind and rainfall throughout Peninsular Malaysia varies from one region to another, depending on the direction of winds and rainfall that occur because of strong wind and the monsoons. Our data consist of daily mean wind and rainfall data from ten stations and covering 25 years period from 1985 to 2009. The purpose of this study is to convert the wind and rainfall data into a smooth curve by using Functional Data Analysis (FDA) method. The Fourier basis is used in this study in which the wind and rainfall data indicate periodic pattern for ten stations. In this method, to avoid such overfitting data, roughness penalty is added to the least square when constructing functional data object from the observed data. By using small basis functions, the difference is very small between with and without roughness penalty, showing that it is safer to smooth only when required. Meanwhile, with large basis functions and the difference of sum of square is very large, roughness penalty should be added in order to obtain optimal fit data. The graphs with contour plot show the relationship between wind and rainfall data, which illustrate the correlation and cross-correlations functions. Functional linear model also presents the relationship that may exist between wind (functional data) and rainfall (scalar response). Square multiple correlations give strong positive linear correlation, which concludes that the rainfall is influenced by the wind speed. 2014 Thesis http://eprints.utm.my/id/eprint/48621/ http://eprints.utm.my/id/eprint/48621/1/WanNorliyanaWanIsmailMFS2014.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:79461?queryType=vitalDismax&query=Statistical+analysis+of+wind+and+rainfall+with+functional+data+analysis+technique&public=true masters Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QC Physics
spellingShingle	QC Physics Wan Ismail, Wan Norliyana Statistical analysis of wind and rainfall with functional data analysis technique
description	The speed of wind and rainfall throughout Peninsular Malaysia varies from one region to another, depending on the direction of winds and rainfall that occur because of strong wind and the monsoons. Our data consist of daily mean wind and rainfall data from ten stations and covering 25 years period from 1985 to 2009. The purpose of this study is to convert the wind and rainfall data into a smooth curve by using Functional Data Analysis (FDA) method. The Fourier basis is used in this study in which the wind and rainfall data indicate periodic pattern for ten stations. In this method, to avoid such overfitting data, roughness penalty is added to the least square when constructing functional data object from the observed data. By using small basis functions, the difference is very small between with and without roughness penalty, showing that it is safer to smooth only when required. Meanwhile, with large basis functions and the difference of sum of square is very large, roughness penalty should be added in order to obtain optimal fit data. The graphs with contour plot show the relationship between wind and rainfall data, which illustrate the correlation and cross-correlations functions. Functional linear model also presents the relationship that may exist between wind (functional data) and rainfall (scalar response). Square multiple correlations give strong positive linear correlation, which concludes that the rainfall is influenced by the wind speed.
format	Thesis
qualification_level	Master's degree
author	Wan Ismail, Wan Norliyana
author_facet	Wan Ismail, Wan Norliyana
author_sort	Wan Ismail, Wan Norliyana
title	Statistical analysis of wind and rainfall with functional data analysis technique
title_short	Statistical analysis of wind and rainfall with functional data analysis technique
title_full	Statistical analysis of wind and rainfall with functional data analysis technique
title_fullStr	Statistical analysis of wind and rainfall with functional data analysis technique
title_full_unstemmed	Statistical analysis of wind and rainfall with functional data analysis technique
title_sort	statistical analysis of wind and rainfall with functional data analysis technique
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2014
url	http://eprints.utm.my/id/eprint/48621/1/WanNorliyanaWanIsmailMFS2014.pdf
_version_	1747817435130494976

Statistical analysis of wind and rainfall with functional data analysis technique

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