Extensions of stability selection using subsamples of observations and covariates

07/18/2014
by   Andre Beinrucker, et al.
0

We introduce extensions of stability selection, a method to stabilise variable selection methods introduced by Meinshausen and Bühlmann (J R Stat Soc 72:417-473, 2010). We propose to apply a base selection method repeatedly to random observation subsamples and covariate subsets under scrutiny, and to select covariates based on their selection frequency. We analyse the effects and benefits of these extensions. Our analysis generalizes the theoretical results of Meinshausen and Bühlmann (J R Stat Soc 72:417-473, 2010) from the case of half-samples to subsamples of arbitrary size. We study, in a theoretical manner, the effect of taking random covariate subsets using a simplified score model. Finally we validate these extensions on numerical experiments on both synthetic and real datasets, and compare the obtained results in detail to the original stability selection method.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/11/2021

Propensity Score Adapted Covariate Selection for Causal Inference

In this paper, we propose a propensity score adapted variable selection ...
research
07/06/2019

The revisited knockoffs method for variable selection in L1-penalised regressions

We consider the problem of variable selection in regression models. In p...
research
11/17/2022

Variable selection for nonlinear Cox regression model via deep learning

Variable selection problem for the nonlinear Cox regression model is con...
research
03/05/2019

Convex Covariate Clustering for Classification

Clustering, like covariate selection for classification, is an important...
research
12/02/2022

Stable Learning via Sparse Variable Independence

The problem of covariate-shift generalization has attracted intensive re...
research
03/25/2022

Sequential matched randomization and a case for covariate-adaptive randomization

Background: Sequential Matched Randomization (SMR) is one of multiple re...
research
02/21/2020

Aggregation of Multiple Knockoffs

We develop an extension of the Knockoff Inference procedure, introduced ...

Please sign up or login with your details

Forgot password? Click here to reset