Abstract
We develop and analyze a framework for two-stage methods with EB-splines, applicable to continuous and discrete approximation problems. In particular, we propose a weighted discrete least squares fit that yields optimal convergence rates for sufficiently dense data on Lipschitz domains in Rd.
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