6533b859fe1ef96bd12b72c7
RESEARCH PRODUCT
Applying differential geometric LARS algorithm to ultra-high dimensional feature space
Luigi AugugliaroAngelo Mineosubject
LARS dimensionality reduction variable selection differential geometrySettore SECS-S/01 - Statisticadescription
Variable selection is fundamental in high-dimensional statistical modeling. Many techniques to select relevant variables in generalized linear models are based on a penalized likelihood approach. In a recent paper, Fan and Lv (2008) proposed a sure independent screening (SIS) method to select relevant variables in a linear regression model defined on a ultrahigh dimensional feature space. Aim of this paper is to define a generalization of the SIS method for generalized linear models based on a differential geometric approach.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2009-01-01 |