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Thesis

Reweighting methods in high dimensional regression

Abstract:

In this thesis, we focus on the application of covariate reweighting with Lasso-style methods for regression in high dimensions, particularly where p

n. We apply a particular focus to the case of sparse regression under a-priori grouping structures.

In such problems, even in the linear case, accurate estimation is difficult. Various authors have suggested ideas such as the Group Lasso and the Sparse Group Lasso, based on convex penalties, or alternatively methods like the...

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Institution:
University of Oxford
Oxford college:
Corpus Christi College
Department:
Mathematical,Physical & Life Sciences Division - Statistics

Contributors

Role:
Supervisor
Publication date:
2012
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
URN:
uuid:26f8541a-9e2d-466a-84aa-e6850c4baba9
Local pid:
ora:7122

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