Posterior contraction rate of sparse latent feature models with application to proteomics

DOI10.1080/24754269.2021.1974664OpenAlexW3198548176MaRDI QIDQ5880101

No author found.

Publication date: 7 March 2023

Published in: Statistical Theory and Related Fields (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1909.09261

zbMATH Keywords

Markov chain Monte CarloIndian buffet processlatent featurehigh dimensionposterior convergencereverse phase protein arrays

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• KEGG
• TCGA-assembler

Cites Work

• Unnamed Item
• Posterior contraction rates of the phylogenetic Indian buffet processes
• Nonparametric Bayesian sparse factor models with application to gene expression modeling
• Needles and straw in a haystack: posterior concentration for possibly sparse sequences
• The consistency of posterior distributions in nonparametric problems
• Posterior contraction in sparse Bayesian factor models for massive covariance matrices
• Gibbs Sampling Methods for Stick-Breaking Priors
• On Bayes procedures

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