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Asymptotically optimal quantization schemes for Gaussian processes on Hilbert spaces

Harald LuschgyGilles PagèsBenedikt Wilbertz — 2010

ESAIM: Probability and Statistics

We describe quantization designs which lead to asymptotically and order optimal functional quantizers for Gaussian processes in a Hilbert space setting. Regular variation of the eigenvalues of the covariance operator plays a crucial role to achieve these rates. For the development of a constructive quantization scheme we rely on the knowledge of the eigenvectors of the covariance operator in order to transform the problem into a finite dimensional quantization problem of normal distributions. ...

Distortion mismatch in the quantization of probability measures

Siegfried GrafHarald LuschgyGilles Pagès — 2008

ESAIM: Probability and Statistics

We elucidate the asymptotics of the -quantization error induced by a sequence of -optimal -quantizers of a probability distribution on d when . In particular we show that under natural assumptions, the optimal rate is preserved as long as (and for every in the case of a compactly supported distribution). We derive some applications of these results to the error bounds for quantization based cubature formulae in numerical integration on d and on the Wiener space.

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