Bayesian multivariate sparse functional principal components analysis with application to longitudinal microbiome multiomics data
DOI10.1214/21-AOAS1587zbMath1498.62227arXiv2102.00067OpenAlexW4297333602MaRDI QIDQ2080741
Chris Elrod, Rob Knight, Jane J. Kim, Wesley K. Thompson, Austin D. Swafford, Lingjing Jiang
Publication date: 10 October 2022
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2102.00067
Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Functional data analysis (62R10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
- Uniform convergence rates for nonparametric regression and principal component analysis in functional/longitudinal data
- Multilevel functional principal component analysis
- Functional data analysis
- Multivariate functional principal component analysis: A normalization approach
- Entropy expressions and their estimators for multivariate distributions
- Relative Entropy Measures of Multivariate Dependence
- Principal component models for sparse functional data
- Shannon Entropy and Mutual Information for Multivariate Skew‐Elliptical Distributions
- On Properties of Functional Principal Components Analysis
- Bayesian correlation estimation
- Functional Data Analysis for Sparse Longitudinal Data
This page was built for publication: Bayesian multivariate sparse functional principal components analysis with application to longitudinal microbiome multiomics data
