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stat.ME2026
Backward Smoothing versus Fixed-Lag Smoothing in Particle Filters
Genshiro Kitagawa
Particle smoothing enables state estimation in nonlinear and non-Gaussian state-space models, but its practical use is often limited by high computational cost. Backward smoothing…
stat.ME2026
Bayesian Optimization of Noisy Log-Likelihoods Evaluated by Particle Filters -- One Parameter Case --
Genshiro Kitagawa
Likelihood functions evaluated using particle filters are typically noisy, computationally expensive, and non-differentiable due to Monte Carlo variability. These characteristics m…