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    On the performances of a new thresholding procedure using tree structure

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    This paper deals with the problem of function estimation. Using the white noise model setting, we provide a method to construct a new wavelet procedure based on thresholding rules which takes advantage of the dyadic structure of the wavelet decomposition. We prove that this new procedure performs very well since, on the one hand, it is adaptive and near-minimax over a large class of Besov spaces and, on the other hand, the maximal functional space (maxiset) where this procedure attains a given rate of convergence is very large. More than this, by studying the shape of its maxiset, we prove that the new procedure outperforms the hard thresholding procedure.Comment: Published in at http://dx.doi.org/10.1214/08-EJS205 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Neutrino Factory Designs and R&D

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    European, Japanese, and US Neutrino Factory designs are presented. The main R&D issues, and the associated R&D programs, are discussed.Comment: Talk presented at the XXth International Conference on Neutrino Physics and Astrophysics, May 25-30, 2002, Munich, Germany. 10 pages, 12 figure

    Thresholding methods to estimate the copula density

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    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

    Thresholding methods to estimate the copula density

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    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

    O.J. FIRESTONE, Problems of Economic Growth

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    Doublet final focus

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    A doublet scheme is designed in a self consistent analytical way for the low b insertion of a m+-m- collider. It assumes focusing strengths of same magnitude and opposite signs in the quadrupoles. At the matching point, the b values are equal and the a values opposite. Two solutions using superconducting or permanent quadrupoles are discussed
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