Bootstrap Markov chain Monte Carlo and optimal solutions for the Law of Categorical Judgment (Corrected)
A novel procedure is described for accelerating the convergence of Markov chain Monte Carlo computations. The algorithm uses an adaptive bootstrap technique to generate candidate steps in the Markov Chain. It is efficient for symmetric, convex probability distributions, similar to multivariate Gauss...
| Автори: | , |
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| Формат: | Working paper |
| Мова: | English |
| Опубліковано: |
2010
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| Предмети: |