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Existence of MLE and posteriors for a recognition-memory model |
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| Authors: | Xiaoyan Lin Dongchu Sun Paul L. Speckman Jeffery N. Rouder |
| Affiliation: | 1. Department of Statistics, University of South Carolina, Columbia, SC 29208, United States;2. School of Finance and Statistics, East China Normal University, Shanghai, 200241, China;3. Department of Statistics, University of Missouri, Columbia, MO 65211, United States;4. Department of Psychological Science, University of Missouri, Columbia, MO 65211, United States |
| 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. |
| Keywords: | Criterion Fixed effect Recognition memory Sensitivity Signal detection |
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