Efficient Estimation and Response Variable Selection in Sparse Partial Envelope Model

Abstract

In this paper, we propose a sparse partial envelope model that performs response variable selection efficiently under the partial envelope model. We discuss its theoretical properties including consistency, an oracle property and the asymptotic distribution of the sparse partial envelope estimator. A large-sample situation and high-dimensional situation are both considered. Numerical experiments demonstrate that the sparse partial envelope estimator has excellent response variable selection performance both in the large-sample situation and the high-dimensional situation. Moreover, simulation studies and real data analysis suggest that the sparse partial envelope estimator has a much more competitive performance than the standard estimator, the oracle partial envelope estimator, the active partial envelope estimator and the sparse envelope estimator, whether it is in the large-sample situation or the high-dimensional situation.

Keywords

• response variable selection
• dimension reduction
• partial envelope model
• Grassmann manifold
• oracle property