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


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