A constraint on extensible quadrature rules
arXiv:1404.5363
Abstract
When the worst case integration error in a family of functions decays as for some and simple averages along an extensible sequence match that rate at a set of sample sizes , then these sample sizes must grow at least geometrically. More precisely, must hold for a value that increases with . This result always rules out arithmetic sequences but never rules out sample size doubling. The same constraint holds in a root mean square setting.
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