Lower Bounds for the Error of Quadrature Formulas for Hilbert Spaces
share
We prove lower bounds for the worst case error of quadrature formulas that use given sample points X_n = { x_1, ... , x_n }. We are mainly interested in optimal point sets X_n, but also prove lower bounds that hold for most randomly selected sets. As a tool, we use a recent result (and extensions thereof) of Vybíral on the positive semi-definiteness of certain matrices related to the product theorem of Schur. The new technique also works for spaces of analytic functions where known methods based on decomposable kernels cannot be applied.
READ FULL TEXT