Fast automatic Bayesian cubature using lattice sampling

Author:

Jagadeeswaran R.,Hickernell Fred J.

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability,Theoretical Computer Science

Reference25 articles.

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3. Cools, R., Nuyens, D. (eds.): Monte Carlo and Quasi-Monte Carlo Methods: MCQMC, Leuven, Belgium, Springer Proceedings in Mathematics and Statistics, 2016, vol. 163. Springer, Berlin (2014)

4. Craven, P., Wahba, G.: Smoothing noisy data with spline functions: estimating the correct degree of smoothing by the method of generalized cross-validation. Numer. Math. 31, 307–403 (1979)

5. Diaconis, P.: Bayesian numerical analysis. In: Gupta, S.S., Berger, J.O. (eds.) Statistical Decision Theory and Related Topics IV, Papers from the 4th Purdue Symposium, West Lafayette, Indiana 1986, vol. 1, pp. 163–175. Springer, New York (1988)

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