Phylogenetically informed Bayesian truncated copula graphical models for microbial association networks
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Publication:2080756
DOI10.1214/21-AOAS1598zbMath1498.62202arXiv2105.05082OpenAlexW3161760927MaRDI QIDQ2080756
Irina Gaynanova, Yang Ni, Hee Cheol Chung
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/2105.05082
Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Probabilistic graphical models (62H22)
Uses Software
Cites Work
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- Extending the rank likelihood for semiparametric copula estimation
- Sparse inverse covariance estimation with the graphical lasso
- Scaling it up: stochastic search structure learning in graphical models
- Copula Gaussian graphical models and their application to modeling functional disability data
- Efficient estimation in the bivariate normal copula model: Normal margins are least favourable
- Inference from iterative simulation using multiple sequences
- High-dimensional semiparametric Gaussian copula graphical models
- Bayesian inference in nonparanormal graphical models
- Graphical models for zero-inflated single cell gene expression
- High-dimensional graphs and variable selection with the Lasso
- Bayesian graphical Lasso models and efficient posterior computation
- Analysis of Phylogenetics and Evolution with R
- Bayesian Inference for General Gaussian Graphical Models With Application to Multivariate Lattice Data
- Model selection and estimation in the Gaussian graphical model
- Hyper Inverse Wishart Distribution for Non-decomposable Graphs and its Application to Bayesian Inference for Gaussian Graphical Models
- Latent Space Approaches to Social Network Analysis
- A Bayesian Graphical Model for ChIP-Seq Data on Histone Modifications
- Latent Network Estimation and Variable Selection for Compositional Data Via Variational EM
- Sparse semiparametric canonical correlation analysis for data of mixed types
- Bayesian Analysis of Binary and Polychotomous Response Data
- Bayesian Inference of Multiple Gaussian Graphical Models
- High Dimensional Semiparametric Latent Graphical Model for Mixed Data
- Covariance selection for nonchordal graphs via chordal embedding