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Doriano Regazzi: The Lasso for Linear Models with within Group Structure
Adviser: Prof. Dr. Sara van de Geer
August 2010
Abstract:
In an high dimensional regression model, we consider the problem of
estimating a grouped parameter vector. We assume there is within group
structure, in the sense that the ordering of the variables within groups ex-
presses their relevance. In this setting, we study two group lasso methods:
the structured group lasso and the weighted group lasso. Our work consists
in the implementation of these two methods in R. First, we prove the con-
vergence of their algorithms. Then, we run simulations and we compare the
two estimators in various situations.
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