Scalable inference for crossed random effects models

DOI10.1093/biomet/asz058zbMath1435.62283arXiv1803.09460OpenAlexW2988654370MaRDI QIDQ5222217

Giacomo Zanella, Gareth O. Roberts, Omiros Papaspiliopoulos

Publication date: 1 April 2020

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1803.09460

zbMATH Keywords

spectral gapGibbs sampleranalysis of varianceBayesian computation

Mathematics Subject Classification ID

Applications of statistics to social sciences (62P25) Analysis of variance and covariance (ANOVA) (62J10)

Related Items

Backfitting for large scale crossed random effects regressions ⋮ Multilevel linear models, Gibbs samplers and multigrid decompositions (with discussion) ⋮ Joint modeling of playing time and purchase propensity in massively multiplayer online role-playing games using crossed random effects ⋮ Estimating promotion effects in email marketing using a large-scale cross-classified Bayesian joint model for nested imbalanced data ⋮ Scalable Bayesian computation for crossed and nested hierarchical models ⋮ Exact convergence analysis for metropolis–hastings independence samplers in Wasserstein distances ⋮ Unnamed Item ⋮ Scalable logistic regression with crossed random effects