Mathematics of Computation

ISSN 1088-6842(online) ISSN 0025-5718(print)



Convexity results and sharp error estimates in approximate multivariate integration

Authors: Allal Guessab and Gerhard Schmeisser
Translated by:
Journal: Math. Comp. 73 (2004), 1365-1384
MSC (2000): Primary 65D30, 65D32, 41A63, 41A44, 41A80; Secondary 26B25, 26D15, 52A40
Published electronically: December 19, 2003
MathSciNet review: 2047091
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Abstract: An interesting property of the midpoint rule and the trapezoidal rule, which is expressed by the so-called Hermite-Hadamard inequalities, is that they provide one-sided approximations to the integral of a convex function. We establish multivariate analogues of the Hermite-Hadamard inequalities and obtain access to multivariate integration formulae via convexity, in analogy to the univariate case. In particular, for simplices of arbitrary dimension, we present two families of integration formulae which both contain a multivariate analogue of the midpoint rule and the trapezoidal rule as boundary cases. The first family also includes a multivariate analogue of a Maclaurin formula and of the two-point Gaussian quadrature formula; the second family includes a multivariate analogue of a formula by P.C. Hammer and of Simpson's rule. In both families, we trace out those formulae which satisfy a Hermite-Hadamard inequality. As an immediate consequence of the latter, we obtain sharp error estimates for twice continuously differentiable functions.

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Additional Information

Allal Guessab
Affiliation: Department of Applied Mathematics, University of Pau, 64000 Pau, France

Gerhard Schmeisser
Affiliation: Mathematical Institute, University of Erlangen-Nuremberg, 91054 Erlangen, Germany

Keywords: Multivariate approximate integration, convex functions, Hermite--Hadamard inequality, error estimates
Received by editor(s): October 24, 2002
Published electronically: December 19, 2003
Article copyright: © Copyright 2003 American Mathematical Society