Regularized bridge-type estimation with multiple penalties

Alessandro Gregorio () and Francesco Iafrate ()
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Alessandro Gregorio: “Sapienza” University of Rome
Francesco Iafrate: “Sapienza” University of Rome

Annals of the Institute of Statistical Mathematics, 2021, vol. 73, issue 5, No 3, 951 pages

Abstract: Abstract The aim of this paper is to introduce an adaptive penalized estimator for identifying the true reduced parametric model under the sparsity assumption. In particular, we deal with the framework where the unpenalized estimator of the structural parameters needs simultaneously multiple rates of convergence (i.e., the so-called mixed-rates asymptotic behavior). We introduce a bridge-type estimator by taking into account penalty functions involving $$\ell ^q$$ ℓ q norms (0

Keywords: High-frequency scheme; Oracle properties; Multidimensional diffusion processes; Prediction accuracy; Penalized estimation; Quasi-likelihood function (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10463-020-00769-w

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