Mathematics – Statistics Theory
Scientific paper
2008-02-18
Journal of Multivariate Analysis 101, 1 (2010) 200-222
Mathematics
Statistics Theory
Scientific paper
10.1016/j.jmva.2009.07.009
This paper deals with the problem of the multivariate copula density estimation. Using wavelet methods we provide two shrinkage procedures based on thresholding rules for which the knowledge of the regularity of the copula density to be estimated is not necessary. These methods, said to be adaptive, are proved to perform very well when adopting the minimax and the maxiset approaches. Moreover we show that these procedures can be discriminated in the maxiset sense. We produce an estimation algorithm whose qualities are evaluated thanks some simulation. Last, we propose a real life application for financial data.
Autin Florent
Pennec Erwan Le
Tribouley Karine
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