Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Sufficient dimension reduction based on distance-weighted discrimination

Randall, Hayley, Artemiou, Andreas and Qiao, Xingye 2020. Sufficient dimension reduction based on distance-weighted discrimination. Scandinavian Journal of Statistics 10.1111/sjos.12484
Item availability restricted.

[img] PDF - Accepted Post-Print Version
Restricted to Repository staff only until 23 July 2021 due to copyright restrictions.

Download (496kB)

Abstract

In this paper we introduce a sufficient dimension reduction (SDR) algorithm based on Distance Weighted Discrimination (DWD). Our methods is shown to be robust on the dimension p of the predictors in our problem, and it also utilizes some new computational results in the DWD literature to propose a computationally faster algorithm than the previous classification-based algorithms in the SDR literature. In addition to the theoretical results of similar methods we prove the consistency of our estimate for divergent number of p. Finally, we demonstrate the advantages of our algorithm using simulated and real datasets.

Item Type: Article
Date Type: Published Online
Status: In Press
Schools: Mathematics
Subjects: Q Science > QA Mathematics
Publisher: Wiley
ISSN: 0303-6898
Funders: EPSRC
Date of First Compliant Deposit: 16 July 2020
Date of Acceptance: 13 July 2020
Last Modified: 16 Sep 2020 09:36
URI: http://orca.cf.ac.uk/id/eprint/133416

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics