Estimating the stillbirth rate for 195 countries using a Bayesian sparse regression model with temporal smoothing

DOI10.1214/21-AOAS1571zbMath1496.62196arXiv2010.03551OpenAlexW3092100803MaRDI QIDQ2080726

Hannah Blencowe, Zhengfan Wang, Leontine Alkema, Miranda J. Fix, Jon Wakefield, Lucia Hug, Danzhen You, Anu Mishra

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/2010.03551

zbMATH Keywords

Bayesian hierarchical modeltime-series analysisBayesian sparsity

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)

Uses Software

• Stan
• RStan
• rstan
• loo

Cites Work

• Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
• Sparsity information and regularization in the horseshoe and other shrinkage priors
• Stan
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• A Bayesian approach to the global estimation of maternal mortality
• Inference from iterative simulation using multiple sequences
• Rank-normalization, folding, and localization: an improved \(\widehat{R}\) for assessing convergence of MCMC (with Discussion)
• Comparison of Bayesian predictive methods for model selection
• Flexible smoothing with P-splines: a unified approach
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

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