Please use this identifier to cite or link to this item:
|Title:||The efficiency of the method of moments estimates for hyperparameters in the empirical Bayes binomial model||Authors:||Lu, W.-S.||Keywords:||Cramér-Rao lower bound
Efficiency and asymptotic efficiency
Empirical Bayes binomial model
Method of moments
|Issue Date:||1999||Citation:||Lu, W.-S. (1999). The efficiency of the method of moments estimates for hyperparameters in the empirical Bayes binomial model. Computational Statistics 14 (2) : 263-276. ScholarBank@NUS Repository.||Abstract:||In the empirical Bayes binomial model of Morris (1983), the Bayes estimate of the binomial proportion parameter has a shrinkage pattern with prior mean p and shrinkage factor b as the hyperparameters. Formulating an empirical Bayes estimate, Morris employs the method of moments to estimate these two hyperparameters. This paper investigates the efficiency/asymptotic efficiency of these estimates relative to the Cramér-Rao lower bound for the variance of unbiased estimates. The efficiency of the estimate of p and the asymptotic efficiency of the estimate of b are mathematically formulated. The estimate of p is at least 95% efficient in all cases, and it becomes perfectly efficient as the parameter b approaches 0 or 1. The estimate of b has a very high asymptotic efficiency in most cases, for example at least 83% when the binomial sample size m ≤ 10; at least 90% when m ≤ 5, and it becomes perfectly asymptotically efficient as the parameter b approaches 1.||Source Title:||Computational Statistics||URI:||http://scholarbank.nus.edu.sg/handle/10635/105414||ISSN:||09434062|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jan 27, 2022
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.