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...
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| Format: | Thesis |
| Idioma: | English |
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2022
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