Fitting semiparametric random effects models to large data sets

DOI10.1093/BIOSTATISTICS/KXM008zbMath1267.62109OpenAlexW2109228565WikidataQ31109055 ScholiaQ31109055MaRDI QIDQ2839002

David B. Dunson, Michael L. Pennell

Publication date: 4 July 2013

Published in: Biostatistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1093/biostatistics/kxm008

zbMATH Keywords

longitudinal datacluster analysisDirichlet processlatent variablesprior elicitationmixed effects models

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50) Nonparametric inference (62G99)

Related Items (7)

Semiparametric Bayesian analysis of high-dimensional censored outcome data ⋮ An application of Dirichlet process in clustering subjects via variance shift models: A course-evaluation study ⋮ Bayesian Inference in Semiparametric Mixed Models for Longitudinal Data ⋮ Sparse variational analysis of linear mixed models for large data sets ⋮ Scalable Bayesian Nonparametric Clustering and Classification ⋮ An approximate posterior simulation for GLMM with large samples ⋮ Bayesian nonparametric clustering for large data sets

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