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An Influence Method for Outliers Detection Applied to Time Series Traffic Data

Watson, S.M., Clark, S.D., Tight, M.R. and Redfern, E. (1992) An Influence Method for Outliers Detection Applied to Time Series Traffic Data. Working Paper. Institute of Transport Studies, University of Leeds , Leeds, UK.

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The applicability of an outlier detection statistic developed for standard time series is assessed in estimating missing values and detecting outliers in traffic count data. The work of Chernick, Downing and Pike (1982) is extended to form a quantitive outlier detection statistic for use with time series data. The statistic is formed from the squared elements of the Influence Function Matrix, where each element of the matrix gives the influence on pk, of a pair of observations at time lag k. Approximate first four moments for the statistic are derived and by fitting Johnson curves to those theoretical moments, critical points are also produced. The statistic is also used to form the basis of an adjustment procedure to treat outliers or estimate missing values in the time series. Chernick et al's (1982) nuclear power data and the Department of Transport's traffic count data are used for practical illustration.

Item Type: Monograph (Working Paper)
Copyright, Publisher and Additional Information: Copyright of the Institute of Transport Studies, University Of Leeds
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)
Depositing User: Adrian May
Date Deposited: 18 May 2007
Last Modified: 06 Jun 2014 05:26
Published Version: http://www.its.leeds.ac.uk/
Status: Published
Publisher: Institute of Transport Studies, University of Leeds
Identification Number: Working Paper 365
URI: http://eprints.whiterose.ac.uk/id/eprint/2206

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