Efficient Estimation and Response Variable Selection in Sparse Partial Envelope Model

Yu Wu and Jing Zhang ()
Additional contact information
Yu Wu: Business School, Nanjing University, Nanjing 210093, China
Jing Zhang: College of Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China

Mathematics, 2024, vol. 12, issue 23, 1-28

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 (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/23/3758/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/23/3758/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2024:i:23:p:3758-:d:1532258

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().