Recently there has been renewed interest in the problem of finding under and over estimations on the set of convex functions to a given nonnegativelinear functional;that is, approximations which estimate always below...
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Recently there has been renewed interest in the problem of finding under and over estimations on the set of convex functions to a given nonnegativelinear functional;that is, approximations which estimate always below (or above) the functional over a family of convex functions. The most important example of such an approximation problem is given by the multidimensional versions of the midpoint (rectangle) rule and the trapezoidal rule, which provide under and over estimations to the true value of the integral on the set of convex functions (also known as the HermiteHadamard inequality). In this paper, we introduce a general method of constructing new families of under/overestimators on the set of convex functions for a general class of linearfunctionals. In particular, under the regularity condition, namely the functions belonging to C-2(Omega) (not necessarily convex), we will show that the error estimations based on such estimators are always controlled by the error associated with using the quadratic function. The result is also extended to the class of Lipschitz functions. We also propose a modified approximation technique to derive a general class of under/over estimators with better error estimates. (C) 2014 Elsevier Inc. All rights reserved.
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