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February 2019 Comment: Unreasonable Effectiveness of Monte Carlo
Art B. Owen
Statist. Sci. 34(1): 29-33 (February 2019). DOI: 10.1214/18-STS676


There is a role for statistical computation in numerical integration. However, the competition from incumbent methods looks to be stiffer for this problem than for some of the newer problems being handled by probabilistic numerics. One of the challenges is the unreasonable effectiveness of the central limit theorem. Another is the unreasonable effectiveness of pseudorandom number generators. A third is the common $O(n^{3})$ cost of methods based on Gaussian processes. Despite these advantages, the classical methods are weak in places where probabilistic methods could bring an improvement.


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Art B. Owen. "Comment: Unreasonable Effectiveness of Monte Carlo." Statist. Sci. 34 (1) 29 - 33, February 2019.


Published: February 2019
First available in Project Euclid: 12 April 2019

zbMATH: 07110671
MathSciNet: MR3938960
Digital Object Identifier: 10.1214/18-STS676

Keywords: probabilistic numerics , quasi-Monte Carlo

Rights: Copyright © 2019 Institute of Mathematical Statistics


Vol.34 • No. 1 • February 2019
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