A comparison of robust bayes and classical estimators for regional lake models of fish response to acidification

Published

Journal Article

Empirical models of fish response to lake acidification were recently fit to a large historical data set from the Adirondack region of the United States using classical and Bayesian methods. The models may be used to predict species presence/absence for brook trout and lake trout as a function of acidā€precipitationā€related water chemistry, using a logistic function. To evaluate the effectiveness of the models in the prediction of presence/absence due to regional lake acidification, new data sets were used for cross validation of the candidate models. Based on this evaluation, the robust Bayes models, which are based on a compromise estimator between Bayes and empirical Bayes, were found to be the best predictors of species presence/absence in lakes. Copyright 1988 by the American Geophysical Union.

Full Text

Duke Authors

Cited Authors

  • Reckhow, KH

Published Date

  • January 1, 1988

Published In

Volume / Issue

  • 24 / 7

Start / End Page

  • 1061 - 1068

Electronic International Standard Serial Number (EISSN)

  • 1944-7973

International Standard Serial Number (ISSN)

  • 0043-1397

Digital Object Identifier (DOI)

  • 10.1029/WR024i007p01061

Citation Source

  • Scopus