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Estimating contaminant loads in rivers: An application of adjusted maximum likelihood to type 1 censored data

Water Resources Research

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DOI: 10.1029/2004WR003833

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Abstract

This paper presents an adjusted maximum likelihood estimator (AMLE) that can be used to estimate fluvial transport of contaminants, like phosphorus, that are subject to censoring because of analytical detection limits. The AMLE is a generalization of the widely accepted minimum variance unbiased estimator (MVUE), and Monte Carlo experiments confirm that it shares essentially all of the MVUE's desirable properties, including high efficiency and negligible bias. In particular, the AMLE exhibits substantially less bias than alternative censored-data estimators such as the MLE (Tobit) or the MLE followed by a jackknife. As with the MLE and the MVUE the AMLE comes close to achieving the theoretical Frechet-Crame??r-Rao bounds on its variance. This paper also presents a statistical framework, applicable to both censored and complete data, for understanding and estimating the components of uncertainty associated with load estimates. This can serve to lower the cost and improve the efficiency of both traditional and real-time water quality monitoring.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Estimating contaminant loads in rivers: An application of adjusted maximum likelihood to type 1 censored data
Series title:
Water Resources Research
DOI:
10.1029/2004WR003833
Volume
41
Issue:
7
Year Published:
2005
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Water Resources Research
First page:
1
Last page:
13
Number of Pages:
13