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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
http://eprints.utm.my/id/eprint/48621/
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
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spelling my.utm.486212020-03-02T07:30:34Z http://eprints.utm.my/id/eprint/48621/ Statistical analysis of wind and rainfall with functional data analysis technique 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 NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/48621/1/WanNorliyanaWanIsmailMFS2014.pdf Wan Ismail, Wan Norliyana (2014) Statistical analysis of wind and rainfall with functional data analysis technique. Masters thesis, Universiti Teknologi Malaysia, Faculty of Science. 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
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
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
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
publishDate 2014
url http://eprints.utm.my/id/eprint/48621/1/WanNorliyanaWanIsmailMFS2014.pdf
http://eprints.utm.my/id/eprint/48621/
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
_version_ 1662754260904837120
score 13.211869

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