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Bayesian synthetic likelihood is a widely used approach for conducting Bayesian analysis in complex models where evaluation of the likelihood is infeasible but simulation from the assumed model is tractable.
Bayesian inference using synthetic likelihood: asymptotics and adjustments
Frazier, D. T., Nott, D. J., Drovandi, C., and Kohn, R. (2021) · 1902
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An, Z., South, L. F., and Drovandi, C. (2019) · 1907
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Efficient Bayesian synthetic likelihood with whitening transformations
Priddle, J. W., Sisson, S. A., Frazier, D. T., and Drovandi, C. (2019) · 1909
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Using bagged posteriors for robust inference and model criticism
Huggins, J. H. and Miller, J. W. (2019) · 1912
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An investigation of the moments of the sample autocovariances and autocorrelations for general arma processes
De Gooijer, J. (1981) · 1981
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On asymptotic normality of limiting density functions with Bayesian implications
Chen, C.-F. (1985) · 1985
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Robustness of ranking and selection rules using generalised g-and-k distributions
Haynes, M. A., MacGillivray, H., and Mengersen, K. (1997) · 1997
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Asymptotics of estimating equations under natural conditions
Yuan, K.-H. and Jennrich, R. I. (1998) · 1998
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Robust approximate Bayesian computation: An adjustment approach
Frazier, D. T., Drovandi, C., and Loaiza-Maya, R. (2020a) · 2008
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Bayesian estimation of quantile distributions
Allingham, D., King, R., and Mengersen, K. (2009) · 2009
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Statistical inference for noisy nonlinear ecological dynamic systems
Wood, S. N. (2010) · 2010
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Likelihood-free Bayesian estimation of multivariate quantile distributions
Drovandi, C. C. and Pettitt, A. N. (2011) · 2011
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The Bernstein-von-Mises theorem under misspecification
Kleijn, B. and van der Vaart, A. (2012) · 2012
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Approximate Bayesian computational methods
Marin, J.-M., Pudlo, P., Robert, C. P., and Ryder, R. J. (2012) · 2012
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Risk of Bayesian inference in misspecified models, and the sandwich covariance matrix
Müller, U. K. (2013) · 2013
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Bayesian synthetic likelihood
Price, L. F., Drovandi, C. C., Lee, A., and Nott, D. J. (2018) · 2018
Later among the works it cites.
Handbook of Approximate Bayesian Computation
Sisson, S. A., Fan, Y., and Beaumont, M. (2018) · 2018
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Bayesian fractional posteriors
Bhattacharya, A., Pati, D., Yang, Y., et al. (2019) · 2019
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Robust Bayesian inference via coarsening
Miller, J. W. and Dunson, D. B. (2019) · 2019
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Robust Bayesian synthetic likelihood via a semi-parametric approach
An, Z., Nott, D. J., and Drovandi, C. (2020) · 2020
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Ecdat: Data Sets for Econometrics
Croissant, Y. and Graves, S. (2020) · 2020
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Relevant statistics for Bayesian model choice
Marin, J.-M., Pillai, N. S., Robert, C. P., and Rousseau, J. (2014) · 2014
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A general framework for updating belief distributions
Bissiri, P. G., Holmes, C. C., and Walker, S. G. (2016) · 2016
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Inconsistency of Bayesian inference for misspecified linear models, and a proposal for repairing it
Grünwald, P., Van Ommen, T., et al. (2017) · 2017
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Model misspecification in approximate Bayesian computation: consequences and diagnostics
Frazier, D. T., Robert, C. P., and Rousseau, J. (2020b)
Cited in the paper.
gk: An R Package for the g-and-k and generalized g-and-h distributions
Prangle, D. (2020) · 2020
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Robust approximate Bayesian inference with synthetic likelihood
Frazier, D. T. and Drovandi, C. (2021) · 2021
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