A principled distance-based prior for the shape of the Weibull model

DOI10.1016/j.spl.2021.109098zbMath1478.62067arXiv2002.06519OpenAlexW3143031816MaRDI QIDQ2244438

Håvard Rue, Haakon Bakka, Janet van Niekerk

Publication date: 12 November 2021

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2002.06519

zbMATH Keywords

survivalBayesian inferenceINLAWeibull modelpenalized complexity prior

Mathematics Subject Classification ID

Bayesian inference (62F15) Reliability and life testing (62N05)

Related Items

A new avenue for Bayesian inference with INLA ⋮ Bayesian survival tree ensembles with submodel shrinkage

Uses Software

• R-INLA

Cites Work

• A note on noninformative priors for Weibull distributions.
• Penalising model component complexity: a principled, practical approach to constructing priors
• Bayesian analysis of the survival function and failure rate of Weibull distribution with censored data
• Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations