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Realization of an outlier detection algorithm using R  

Song, Gyu-Moon (Department of Statistics, Keimyung University)
Moon, Ji-Eun (Department of Statistics, Keimyung University)
Park, Cheol-Yong (Department of Statistics, Keimyung University)
Publication Information
Journal of the Korean Data and Information Science Society / v.22, no.3, 2011 , pp. 449-458 More about this Journal
Abstract
Illegal waste dumping is one of the major problems that the government agency monitoring water quality has to face. Recently government agency installed COD (chemical oxygen demand) auto-monitering machines in river. In this article we provide an outlier detection algorithm using R based on the time series intervention model that detects some outlier values among those COD time series values generated from an auto-monitering machine. Through this algorithm using R, we can achieve an automatic algorithm that does not need manual intervention in each step, and that can further be used in simulation study.
Keywords
Chemical oxygen demand; outlier detection; time series intervention model;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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