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Adaptive Minimax Estimation over Sparse lq-Hulls

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Author Info

  • Zhan Wang
  • Sandra Paterlini

    ()

  • Fuchang Gao
  • Yuhong Yang

Abstract

Given a dictionary of Mn initial estimates of the unknown true regression function, we aim to construct linearly aggregated estimators that target the best performance among all the linear combinations under a sparse q-norm (0

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Bibliographic Info

Paper provided by University of Modena and Reggio E., Dept. of Economics in its series Center for Economic Research (RECent) with number 078.

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Length: pages 78
Date of creation: Jan 2012
Date of revision:
Handle: RePEc:mod:recent:078

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Web page: http://www.recent.unimore.it/
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Related research

Keywords: minimax risk; adaptive estimation; sparse lq-constraint; linear combining; aggregation; model mixing; model selection;

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  1. Zhan Wang & Sandra Paterlini & Fuchang Gao & Yuhong Tang, 2012. "Adaptive Minimax Estimation over Sparse l q-Hulls," Department of Economics 0681, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
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Cited by:
  1. Zhan Wang & Sandra Paterlini & Fuchang Gao & Yuhong Tang, 2012. "Adaptive Minimax Estimation over Sparse l q-Hulls," Department of Economics 0681, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".

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