Consistent selection via the Lasso for high dimensional approximating regression models

@inproceedings{Bunea2008ConsistentSV,
  title={Consistent selection via the Lasso for high dimensional approximating regression models},
  author={Florentina Bunea},
  year={2008}
}
In this article we investigate consistency of selection in regression models via the popular Lasso method. Here we depart from the traditional linear regression assumption and consider approximations of the regression function f with elements of a given dictionary of M functions. The target for consistency is the index set of those functions from this dictionary that realize the most parsimonious approximation to f among all linear combinations belonging to an L2 ball centered at f and of… CONTINUE READING

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