6533b836fe1ef96bd12a1b5e
RESEARCH PRODUCT
DgCox: a differential geometric approach for high-dimensional Cox proportional hazard models
E WitL AugugliaroF AbegazJ Gonzalezsubject
Proportional hazard modelling least angle regression differential geometry sparse inferenceSettore SECS-S/01 - Statisticadescription
Many clinical and epidemiological studies rely on survival modelling to detect clinically relevant factors that affect various event histories. With the introduction of high-throughput technologies in the clinical and even large-scale epidemiological studies, the need for inference tools that are able to deal with fat data-structures, i.e., relatively small number of observations compared to the number of features, is becoming more prominent. This paper will introduce a principled sparse inference methodology for proportional hazards modelling, based on differential geometrical analyses of the high-dimensional likelihood surface.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-01-01 |