| Autor: |
Hamada, M. S., Graves, T. L., Hengartner, N. W., Higdon, D. M., Huzurbazar, A. V., Lawrence, E. C., Linkletter, C. D., Reese, C. S., Scott, D. W., Sitter, R. R., Warr, R. L., Williams, B. J. |
| Rok vydání: |
2020 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
This article presents a Bayesian inferential method where the likelihood for a model is unknown but where data can easily be simulated from the model. We discretize simulated (continuous) data to estimate the implicit likelihood in a Bayesian analysis employing a Markov chain Monte Carlo algorithm. Three examples are presented as well as a small study on some of the method's properties. |
| Databáze: |
arXiv |
| Externí odkaz: |
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