Jan. 1, 2024, midnight | Aki Vehtari, Daniel Simpson, Andrew Gelman, Yuling Yao, Jonah Gabry

JMLR www.jmlr.org

Importance weighting is a general way to adjust Monte Carlo integration to account for draws from the wrong distribution, but the resulting estimate can be highly variable when the importance ratios have a heavy right tail. This routinely occurs when there are aspects of the target distribution that are not well captured by the approximating distribution, in which case more stable estimates can be obtained by modifying extreme importance ratios. We present a new method for stabilizing importance weights using …

distribution general importance integration pareto sampling

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