Sequential Monte Carlo for Bayesian Inference
MATLAB and Python 3 software for Bayesian inference of engineering models using the Sequential Monte Carlo (SMC) method.
Requirements
MATLAB, incl. Statistical toolbox, ERADist and ERANataf probability distribution classes
Python 3
Documentation & background
Del Moral P., Doucet A. , Jasra A. (2006). Sequential monte carlo samplers, Journal of the Royal Statistical Society. Series B (Statistical Methodology), 68(3): 411-436
Jasra A. et al. (2011). Inference for Levy-driven stochastic volatility models via adaptive sequential Monte Carlo. Scand. J. Stat. 38(1): 1-22
Papaioannou I., Papadimitriou, C., Straub D. (2016). Sequential importance sampling for structural reliability analysis. Structural Safety 62: 66-75.
Kamariotis A., Sardi L., Papaioannou I., Chatzi E., Straub D. (2022). On off-line and on-line Bayesian filtering for uncertainty quantification of structural deterioration, arXiv:2205.03478