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Evaluating water quality using power priors to incorporate historical information
Author(s) -
Duan Yuyan,
Ye Keying,
Smith Eric P.
Publication year - 2006
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.752
Subject(s) - prior probability , bayesian probability , computer science , range (aeronautics) , water quality , statistics , data mining , quality (philosophy) , sample size determination , sample (material) , prior information , data quality , econometrics , mathematics , artificial intelligence , ecology , philosophy , materials science , chemistry , epistemology , chromatography , composite material , biology , metric (unit) , operations management , economics
Abstract To assess water quality standards, measurements of water quality under the Clean Water Act are collected on a regular basis over a period of time. The data are analyzed to evaluate the percentage of samples exceeding the standard. One problem is that current data are limited by the time range and consequently the sample size is inadequate to provide necessary precision in parameter estimation. To address this issue, we present a Bayesian approach using a power prior to incorporate historical data and/or the data collected at adjacent stations. We develop a modified power prior approach and discuss its properties under the normal mean model. Several sets of water quality data are studied to illustrate the implementation of the power prior approach and its differences from alternative methods. Copyright © 2005 John Wiley & Sons, Ltd.