A comparison of various imputation methods for missing values in air quality data

Nuryazmin Ahmat Zainuri, and Abdul Aziz Jemain, and Nora Muda, (2015) A comparison of various imputation methods for missing values in air quality data. Sains Malaysiana, 44 (3). pp. 449-456. ISSN 0126-6039

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Official URL: http://www.ukm.my/jsm/

Abstract

This paper presents various imputation methods for air quality data specifically in Malaysia. The main objective was to select the best method of imputation and to compare whether there was any difference in the methods used between stations in Peninsular Malaysia. Missing data for various cases are randomly simulated with 5, 10, 15, 20, 25 and 30% missing. Six methods used in this paper were mean and median substitution, expectation-maximization (EM) method, singular value decomposition (SVD), K-nearest neighbour (KNN) method and sequential K-nearest neighbour (SKNN) method. The performance of the imputations is compared using the performance indicator: The correlation coefficient (R), the index of agreement (d) and the mean absolute error (MAE). Based on the result obtained, it can be concluded that EM, KNN and SKNN are the three best methods. The same result are obtained for all the eight monitoring station used in this study.

Item Type:Article
Keywords:Imputation techniques; missing data; performance indicators
Journal:Sains Malaysiana
ID Code:8488
Deposited By: ms aida -
Deposited On:13 Apr 2015 04:37
Last Modified:14 Dec 2016 06:47

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