Title: Estimating Derivatives of Noisy Simulations
Authors: Jorge J. Moré, Stefan M. Wild
Abstract: We employ recent work on computational noise to obtain near-optimal difference estimates of the derivative of a noisy function. Our analysis relies on a stochastic model of the noise without assuming a specific form of distribution. We use this model to derive theoretical bounds for the errors in the difference estimates and obtain an easily computable difference parameter that is provably near-optimal. Numerical results closely resemble the theory and show that we obtain accurate derivative estimates even when the noisy function is deterministic.
Keywords: Computational Noise, Deterministic Simulations, Finite Difference Derivatives
Thanks: This work was supported by the Office of Advanced Scientific Computing Research, Office of Science, U.S. Department of Energy, under Contract DE-AC02-06CH11357.
Status: Appears in ACM Trans. Math. Softw., Vol. 38 (3), pp. 1-21, 2012.
Link: [DOI:10.1145/2168773.2168777 ]
Additional information, including codes and data, can be found on our Estimating Computational Noise page
    author      = {Jorge J. Mor\'e and Stefan M. Wild},
    title 	= {Estimating Derivatives of Noisy Simulations},
    journal 	= {ACM Transactions on Mathematical Software},
    issue_date 	= {April 2012},
    volume 	= {38},
    number 	= {3},
    year 	= {2012},
    pages 	= {19:1--19:21},
    doi 	= {10.1145/2168773.2168777}

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