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Estimation of descriptive statistics for multiply censored water quality data

Water Resources Research

By:
and
https://doi.org/10.1029/WR024i012p01997

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Abstract

This paper extends the work of Gilliom and Helsel (1986) on procedures for estimating descriptive statistics of water quality data that contain “less than” observations. Previously, procedures were evaluated when only one detection limit was present. Here we investigate the performance of estimators for data that have multiple detection limits. Probability plotting and maximum likelihood methods perform substantially better than simple substitution procedures now commonly in use. Therefore simple substitution procedures (e.g., substitution of the detection limit) should be avoided. Probability plotting methods are more robust than maximum likelihood methods to misspecification of the parent distribution and their use should be encouraged in the typical situation where the parent distribution is unknown. When utilized correctly, less than values frequently contain nearly as much information for estimating population moments and quantiles as would the same observations had the detection limit been below them.

Additional publication details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Estimation of descriptive statistics for multiply censored water quality data
Series title:
Water Resources Research
DOI:
10.1029/WR024i012p01997
Volume:
24
Issue:
12
Year Published:
1988
Language:
English
Publisher:
American Geophysical Union
Description:
8 p.
First page:
1997
Last page:
2004