Integration with an Adaptive Harmonic Mean Algorithm
作者： Vasyl Hafych , Rafael C. Schick , Rafael C. Schick , Marco Szalay , Philipp Eller
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摘要: Numerically estimating the integral of functions in high dimensional spaces is a non-trivial task. A oft-encountered example calculation marginal likelihood Bayesian inference, context where sampling algorithm such as Markov Chain Monte Carlo provides samples function. We present an Adaptive Harmonic Mean Integration (AHMI) algorithm. Given drawn according to probability distribution proportional function, will estimate function and uncertainty by applying harmonic mean estimator adaptively chosen regions parameter space. describe its mathematical properties, report results using it on multiple test cases.
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