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Detecting Outliers in Time Series Data

 

作者: MichaelR. Chernick,   DarrylJ. Downing,   DavidH. Pike,  

 

期刊: Journal of the American Statistical Association  （Taylor Available online 1982）
卷期: Volume 77, issue 380  

页码: 743-747

 

ISSN:0162-1459

 

年代: 1982

 

DOI:10.1080/01621459.1982.10477880

 

出版商: Taylor & Francis Group

 

关键词: Autocorrelation;Influence function;Stationary time series;Outliers

 

数据来源: Taylor

 

摘要:

Occasional large errors in data can have drastic effects on estimates for such quantities as correlation coefficients, regression coefficients, and spectral density estimates. In this article we investigate the effect of outliers on time series data by considering the influence function for the autocorrelationsp(k) of a stationary time series. This influence function matrix is applied to simulated data, to power plant data, and to inventory data on nuclear materials.

 

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