You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Estimation and Confidence Intervals for Empirical Mixing Distributions
William A. Link and John R. Sauer
Vol. 51, No. 3 (Sep., 1995), pp. 810-821
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/2532983
Page Count: 12
You can always find the topics here!Topics: Population estimates, Statistical estimation, Estimators, Confidence interval, Species, Bayes estimators, Maximum likelihood estimation, Interval estimators, Ducks, Gaussian distributions
Were these topics helpful?See somethings inaccurate? Let us know!
Select the topics that are inaccurate.
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
Questions regarding collections of parameter estimates can frequently be expressed in terms of an empirical mixing distribution (EMD). This report discusses empirical Bayes estimation of an EMD, with emphasis on the construction of interval estimates. Estimation of the EMD is accomplished by substitution of estimates of prior parameters in the posterior mean of the EMD. This procedure is examined in a parametric model (the normal-normal mixture) and in a semi-parametric model. In both cases, the empirical Bayes bootstrap of Laird and Louis (1987, Journal of the American Statistical Association 82, 739-757) is used to assess the variability of the estimated EMD arising from the estimation of prior parameters. The proposed methods are applied to a meta-analysis of population trend estimates for groups of birds.
Biometrics © 1995 International Biometric Society