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Statistical analysis of water-quality data containing multiple detection limits: S-language software for regression on order statistics

Computers and Geosciences

By:
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DOI: 10.1016/j.cageo.2005.03.012

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Abstract

Trace contaminants in water, including metals and organics, often are measured at sufficiently low concentrations to be reported only as values below the instrument detection limit. Interpretation of these "less thans" is complicated when multiple detection limits occur. Statistical methods for multiply censored, or multiple-detection limit, datasets have been developed for medical and industrial statistics, and can be employed to estimate summary statistics or model the distributions of trace-level environmental data. We describe S-language-based software tools that perform robust linear regression on order statistics (ROS). The ROS method has been evaluated as one of the most reliable procedures for developing summary statistics of multiply censored data. It is applicable to any dataset that has 0 to 80% of its values censored. These tools are a part of a software library, or add-on package, for the R environment for statistical computing. This library can be used to generate ROS models and associated summary statistics, plot modeled distributions, and predict exceedance probabilities of water-quality standards. ?? 2005 Elsevier Ltd. All rights reserved.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Statistical analysis of water-quality data containing multiple detection limits: S-language software for regression on order statistics
Series title:
Computers and Geosciences
DOI:
10.1016/j.cageo.2005.03.012
Volume
31
Issue:
10
Year Published:
2005
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
First page:
1241
Last page:
1248
Number of Pages:
8