Projects per year
Abstract
Canonical correlation analysis (CCA) is a popular statistical tool in multivariate analysis. A regularized version is often used to stabilize the estimate. Motivated by recent interests in sketching estimates for linear regression problems which try to address the computational problem associated with massive data sets, here we investigate the sketched estimation for CCA, which includes the random subsampling approach as a special case. Some theoretical results are established based on perturbation theory. The method is also illustrated via some Monte Carlo studies and a real data analysis. © 2022 Taylor & Francis Group, LLC
Original language | English |
---|---|
Pages (from-to) | 6960-6971 |
Journal | Communications in Statistics - Theory and Methods |
Volume | 52 |
Issue number | 19 |
Online published | 18 May 2022 |
DOIs | |
Publication status | Published - 2023 |
Research Keywords
- Canonical correlation analysis
- random sketching
- ridge regularization
Fingerprint
Dive into the research topics of 'Sketched approximation of regularized canonical correlation analysis'. Together they form a unique fingerprint.Projects
- 2 Finished
-
GRF: Low-rank tensor as a Dimension Reduction Tool in Complex Data Analysis
LIAN, H. (Principal Investigator / Project Coordinator)
1/01/20 → 28/11/24
Project: Research
-
GRF: Divide and Conquer in High-dimensional Statistical Models
LIAN, H. (Principal Investigator / Project Coordinator)
1/10/18 → 24/08/23
Project: Research