Semiparametric partial common principal component analysis for covariance matrices-Reference-Cited by-同舟云学术

Semiparametric partial common principal component analysis for covariance matrices

Published:2020-10-10 Issue:4 Volume:77 Page:1175-1186
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biometrics

Author:

Wang Bingkai¹^ORCID,Luo Xi²,Zhao Yi³^ORCID,Caffo Brian¹

Affiliation:

1. Johns Hopkins Bloomberg School of Public Health Baltimore Maryland

2. The University of Texas Health Science Center at Houston School of Public Health Houston Texas

3. Indiana University School of Medicine Indianapolis Indiana

Funder

National Institute of Biomedical Imaging and Bioengineering

National Institute of Neurological Disorders and Stroke

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/biom.13369

Reference32 articles.

1. Banded regularization of autocovariance matrices in application to parameter estimation and forecasting of time series

2. Spectral models for covariance matrices

3. Estimating common principal components in high dimensions

4. The organization of the human cerebellum estimated by intrinsic functional connectivity

5. Population Value Decomposition, a Framework for the Analysis of Image Populations

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Bayesian estimation of covariate assisted principal regression for brain functional connectivity;Biostatistics;2024-07-09

2. Filtrated common functional principal component analysis of multigroup functional data;The Annals of Applied Statistics;2024-06-01

3. Regression models for partially localized fMRI connectivity analyses;2023-04-20

4. Two-stage linked component analysis for joint decomposition of multiple biologically related data sets;Biostatistics;2022-03-31