Outlier detection in environmental monitoring network data: an application to ambient ozone measurements for Houston, Texas. (English) Zbl 1101.62113
Summary: This paper develops methodology for detecting outliers in environmental network data. Our methods stepwise model the following attributes of the data observed over space and time: (seasonal) mean, heteroscedasticity, non-local space-time interactions, and local space-time interactions. Residuals from a combined model are used to construct multivariate control charts to detect possible outliers.
MSC:
| 62P12 | Applications of statistics to environmental and related topics |
| 62M10 | Time series, auto-correlation, regression, etc. in statistics (GARCH) |
| 65C60 | Computational problems in statistics (MSC2010) |
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