| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10525816 | Statistics & Probability Letters | 2013 | 7 Pages |
Abstract
Necessary and sufficient conditions are developed for the existence of the maximum likelihood estimate (MLE) for a recognition-memory model. The propriety of posteriors is shown for a class of bounded priors. Under a constant prior, an easy-to-implement Gibbs sampler is developed and illustrated via a real data set.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Xiaoyan Lin, Dongchu Sun, Paul L. Speckman, Jeffery N. Rouder,