Загрузка...
Markov chain Monte Carlo without likelihoods
Many stochastic simulation approaches for generating observations from a posterior distribution depend on knowing a likelihood function. However, for many complex probability models, such likelihoods are either impossible or computationally prohibitive to obtain. Here we present a Markov chain Monte...
Сохранить в:
| Главные авторы: | , , , |
|---|---|
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
National Academy of Sciences
2003
|
| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC307566/ https://ncbi.nlm.nih.gov/pubmed/14663152 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.0306899100 |
| Метки: |
Добавить метку
Нет меток, Требуется 1-ая метка записи!
|