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Multivariate intensity estimation via hyperbolic wavelet selection

Presented by: 
Nathalie Akakpo
Thursday 25th January 2018 - 11:00 to 12:00
INI Seminar Room 2
We propose a new statistical procedure that can in some sense overcome the curse of dimensionality without structural assumptions on the function to estimate. It relies on a least-squares type penalized criterion and a new collection of models built from hyperbolic biorthogonal wavelet bases. We study its properties in a unifying intensity estimation framework, where an oracle-type inequality and adaptation to mixed dominating smoothness are shown to hold. We also explain how to implement the estimator with an algorithm whose complexity is manageable. (Reference: JMVA, Volume 161, p.32-57)

University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons