Sequential Monte Carlo for cut-Bayesian posterior computation
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DOI: 10.1007/s00180-024-01576-0
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- Liang, Faming & Liu, Chuanhai & Carroll, Raymond J., 2007. "Stochastic Approximation in Monte Carlo Computation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 305-320, March.
- Garland Durham & John Geweke, 2014. "Adaptive Sequential Posterior Simulators for Massively Parallel Computing Environments," Advances in Econometrics, in: Bayesian Model Comparison, volume 34, pages 1-44, Emerald Group Publishing Limited.
- Higdon, Dave & Gattiker, James & Williams, Brian & Rightley, Maria, 2008. "Computer Model Calibration Using High-Dimensional Output," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 570-583, June.
- Pierre E. Jacob & John O’Leary & Yves F. Atchadé, 2020. "Unbiased Markov chain Monte Carlo methods with couplings," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 543-600, July.
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