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Published September 2004 | public
Journal Article

Sharp bounds under contaminated or corrupted sampling with verification, with an application to environmental pollutant data


Let F denote a distribution of interest and G a possibly spurious distribution. This article derives and nonparametrically estimates sharp bounds on characteristics of F when the data are a mixture of F and G, and a fraction of the data is verified to be from F. Contaminated and corrupted mixtures, with and without monotonicity restrictions, are analyzed. The methods are particularly useful in analyzing environmental pollutant measurements obtained using gas chromatography-mass spectroscopy. Results are applied to measurements of organic pollutant concentrations from the Love Canal. We argue that a corruption with monotonic verification model may be the most appropriate model for this type of data.

Additional Information

© 2004 American Statistical Association and the International Biometric Society. Received 15 July 2003; Revised 15 December 2003. We thank Diane Lambert for providing the organic pollutant data analyzed in this article. We also thank Nathan Dalleska, Director of the Environmental Analysis Center at the California Institute of Technology, for sharing his insights about gas chromatography-mass spectroscopy.

Additional details

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October 19, 2023