Approximate Bayesian inference for mixture cure models
DOI10.1007/s11749-019-00679-xzbMath1458.62225arXiv1806.09362OpenAlexW2977014755WikidataQ127210240 ScholiaQ127210240MaRDI QIDQ2220802
E. Lázaro, Carmen Armero, Virgilio Gómez-Rubio
Publication date: 25 January 2021
Published in: Test (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1806.09362
survival analysisGibbs samplingaccelerated failure time mixture cure modelscomplete and marginal likelihood functionproportional hazards mixture cure models
Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Estimation in survival analysis and censored data (62N02) Reliability and life testing (62N05)
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Bayesian thinking, modeling and computation.
- Markov chain Monte Carlo with the integrated nested Laplace approximation
- Inference from iterative simulation using multiple sequences
- Approximate Bayesian Inference for Survival Models
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- Limited Failure Population Life Tests: Application to Integrated Circuit Reliability
- Dealing With Label Switching in Mixture Models
- Gaussian Markov Random Fields
- Estimating and modeling the cure fraction in population-based cancer survival analysis
- Geoadditive Survival Models
- Bayesian survival analysis
This page was built for publication: Approximate Bayesian inference for mixture cure models