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The Replacement of Missing Values of Continous Air Pollution Monitoring Data using Mean Top Bottom Imputation technique

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Main Authors: Norazian, Mohamed Noor, Ahmad Shukri, Yahaya, Nor Azam, Ramli, Mohd Mustafa, Al Bakri Abdullah
Format: Article
Language:English
Published: Kolej Universiti Kejuruteraan Utara Malaysia 2008
Subjects:
Missing values
Missing observations (Statistics)
Mathematical statistics
Electronic instruments
Multiple imputation (Statistics)
Estimation theory
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/2200
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spelling my.unimap-22002009-04-16T03:25:48Z The Replacement of Missing Values of Continous Air Pollution Monitoring Data using Mean Top Bottom Imputation technique Norazian, Mohamed Noor Ahmad Shukri, Yahaya Nor Azam, Ramli Mohd Mustafa, Al Bakri Abdullah Missing values Missing observations (Statistics) Mathematical statistics Electronic instruments Multiple imputation (Statistics) Estimation theory Link to publisher's homepage at http://www.unimap.edu.my/ Air pollutants data such as PM10 carbon monoxide, sulphur dioxide and ozone concentration were obtained from automated monitoring stations. These data usually contain missing values that can cause bias due to systematic differents between observed and unobserved data. Therefore, it is impirtant to find the best way to estimate these missing values to ensure that the data analyzed are of high precision. This paper focuses on the usage of mean top bottom imputation technique to replace the missing values. Three performance indicators were calculated in order to describe the goodness of fit of this technique. In order to test the efficiency of the method applied, PM10 monitoring dataset for Kuala Lumpur was used as case study. Three distributions that are Weibull, gamma and lognormal were fitted to the datasets after replacement of missing values using mean top bottom method and performance indicators were calculated to describe the qualities of the distributions. The results show that mean top bottom method gives very good performances at low percentage of missing data but the performances slightly decreased at higher degree of complexity. It was found that gamma distribution is the most appropriate distribution representing PM10 emissions in Kuala Lumpur. 2008-09-15T02:33:23Z 2008-09-15T02:33:23Z 2006 Article Journal of Engineering Research and Education, vol. 3, 2006, pages 96-105. 1823-2981 http://hdl.handle.net/123456789/2200 http://www.unimap.edu.my/ en Kolej Universiti Kejuruteraan Utara Malaysia
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Missing values
Missing observations (Statistics)
Mathematical statistics
Electronic instruments
Multiple imputation (Statistics)
Estimation theory
spellingShingle Missing values
Missing observations (Statistics)
Mathematical statistics
Electronic instruments
Multiple imputation (Statistics)
Estimation theory
Norazian, Mohamed Noor
Ahmad Shukri, Yahaya
Nor Azam, Ramli
Mohd Mustafa, Al Bakri Abdullah
The Replacement of Missing Values of Continous Air Pollution Monitoring Data using Mean Top Bottom Imputation technique
description Link to publisher's homepage at http://www.unimap.edu.my/
format Article
author Norazian, Mohamed Noor
Ahmad Shukri, Yahaya
Nor Azam, Ramli
Mohd Mustafa, Al Bakri Abdullah
author_facet Norazian, Mohamed Noor
Ahmad Shukri, Yahaya
Nor Azam, Ramli
Mohd Mustafa, Al Bakri Abdullah
author_sort Norazian, Mohamed Noor
title The Replacement of Missing Values of Continous Air Pollution Monitoring Data using Mean Top Bottom Imputation technique
title_short The Replacement of Missing Values of Continous Air Pollution Monitoring Data using Mean Top Bottom Imputation technique
title_full The Replacement of Missing Values of Continous Air Pollution Monitoring Data using Mean Top Bottom Imputation technique
title_fullStr The Replacement of Missing Values of Continous Air Pollution Monitoring Data using Mean Top Bottom Imputation technique
title_full_unstemmed The Replacement of Missing Values of Continous Air Pollution Monitoring Data using Mean Top Bottom Imputation technique
title_sort replacement of missing values of continous air pollution monitoring data using mean top bottom imputation technique
publisher Kolej Universiti Kejuruteraan Utara Malaysia
publishDate 2008
url http://dspace.unimap.edu.my/xmlui/handle/123456789/2200
_version_ 1643787525808979968
score 13.214268

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