6533b7d4fe1ef96bd1262e1d
RESEARCH PRODUCT
An efficient algorithm to estimate the sparse group structure of an high-dimensional generalized linear model
Luigi AugugliaroAngelo Mineosubject
Group lassoGeneralized linear modelDifferential geometrySettore SECS-S/01 - Statisticadglardescription
Massive regression is one of the new frontiers of computational statistics. In this paper we propose a generalization of the group least angle regression method based on the differential geometrical structure of a generalized linear model specified by a fixed and known group structure of the predictors. An efficient algorithm is also proposed to compute the proposed solution curve.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-01-01 |