Adaptive signal recovery with Subbotin noise

Adaptive signal recovery with Subbotin noise

In this article, we study the problem of high-dimensional variable selection. Specifically, we consider a single vector X from a sparse sequence model with Subbotin noise and derive the regions of variable selection with respect to a Hamming loss function.

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Veröffentlicht in:Statistics & probability letters 2023-05, Vol.196, p.109791, Article 109791
Hauptverfasser: Miller, Joshua C., Stepanova, Natalia A.
Format: Artikel
Sprache:eng
Schlagworte:
Adaptation
Almost full selector
Exact selector
Sparsity
Subbotin distribution
Variable selection
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Beschreibung
Zusammenfassung:In this article, we study the problem of high-dimensional variable selection. Specifically, we consider a single vector X from a sparse sequence model with Subbotin noise and derive the regions of variable selection with respect to a Hamming loss function.
ISSN:0167-7152
1879-2103
DOI:10.1016/j.spl.2023.109791