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Multivariate intensity estimation via hyperbolic wavelet selection

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  • Akakpo, Nathalie

Abstract

We propose a new statistical procedure that can 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 smoothness are shown to hold. We also show how to implement the estimator with an algorithm whose complexity is manageable.

Suggested Citation

  • Akakpo, Nathalie, 2017. "Multivariate intensity estimation via hyperbolic wavelet selection," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 32-57.
    • Handle: RePEc:eee:jmvana:v:161:y:2017:i:c:p:32-57
    DOI: 10.1016/j.jmva.2017.07.005
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