Robust Bayesian synthetic likelihood via a semi-parametric approach

Bayesian synthetic likelihood (BSL) is now a well-established method for performing approximate Bayesian parameter estimation for simulation-based models that do not possess a tractable likelihood function. BSL approximates an intractable likelihood function of a carefully chosen summary statistic a...

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Veröffentlicht in:	Statistics and computing 2020-05, Vol.30 (3), p.543-557
Hauptverfasser:	An, Ziwen, Nott, David J., Drovandi, Christopher
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Bayesian analysis Computer simulation Covariance matrix Mathematics and Statistics Normal distribution Normality Parameter estimation Parametric statistics Probability and Statistics in Computer Science Robustness Statistical analysis Statistical Theory and Methods Statistics Statistics and Computing/Statistics Programs Test procedures
Online-Zugang:	Volltext
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