Likelihood-free Bayesian inference for dynamic, stochastic simulators in the social sciences
<p>Simulation models – such as agent-based models (abms) in the social sciences – are now used widely across scientific and commercial domains. However, such models often lack a tractable likelihood function, precluding standard likelihood-based statistical inference. In response to this chall...
| Autor principal: | |
|---|---|
| Otros Autores: | |
| Formato: | Tesis |
| Lenguaje: | English |
| Publicado: |
2022
|
| Materias: |