Abstract We provide an algorithm to approximate a finitely supported discrete measureμby a measureνNcorresponding to a set ofNpoints so that the total variation betweenμandνNhas an upper bound. As a consequence ifμis a (finite or infinitely supported) discrete probability measure on [0, 1]dwith a sufficient decay rate on the weights of each point, thenμcan be approximated byνNwith total variation, and hence star-discrepancy, bounded above by (logN)N−1. Our result improves, in the discrete case, recent work by Aistleitner, Bilyk, and Nikolov who show that for any normalized Borel measureμ, there exist finite sets whose star-discrepancy with respect toμis at most {\left( {\log \,N} \right)^{d - {1 \over 2}}}{N^{ - 1}}. Moreover, we close a gap in the literature for discrepancy in the cased=1 showing both that Lebesgue is indeed the hardest measure to approximate by finite sets and also that all measures without discrete components have the same order of discrepancy as the Lebesgue measure.
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The effect of adding mass points on bounds for orthogonal polynomials
Let ν be a positive measure supported on [-1,1], with infinitely many points in its support. Let {p_{n}(ν,x)}_{n≥0} be its sequence of orthonormal polynomials. Suppose we add masspoints at ±1, giving a new measure μ=ν+Mδ₁+Nδ₋₁. How much larger can |p_{n}(μ,0)| be than |p_{n}(ν,0)|? We study this question for symmetric measures, and give more precise results for ultraspherical weights. Under quite general conditions, such as ν lying in the Nevai class, it turns out that the growth is no more than 1+o(1) as n→∞.
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- Award ID(s):
- 1800251
- PAR ID:
- 10315033
- Date Published:
- Journal Name:
- Dolomites Research Notes on Approximation
- Volume:
- 14
- ISSN:
- 2035-6803
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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