Bayesian semiparametric modeling of survival data based on mixtures of \(B\)-spline distributions

DOI10.1016/j.csda.2010.09.007zbMath1328.65022OpenAlexW2038890372WikidataQ123417526 ScholiaQ123417526MaRDI QIDQ901494

Bo Cai, Renate Meyer

Publication date: 12 January 2016

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2010.09.007

zbMATH Keywords

B-splinesmixture modelbaseline hazard functionBayesian semiparametric modelstratified data

Mathematics Subject Classification ID

Estimation in survival analysis and censored data (62N02)

Related Items

Bayesian Spatial Survival Models ⋮ Bayesian nonparametric spectral density estimation using B-spline priors ⋮ A flexible family of density functions ⋮ Hierarchical failure time regression using mixtures for classification of the immune response of atlantic salmon

Uses Software

• SemiPar
• FITPACK

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Adaptive rejection Metropolis sampling using Lagrange interpolation polynomials of degree 2
• Reparameterisation issues in mixture modelling and their bearing on MCMC algorithms.
• Inference from iterative simulation using multiple sequences
• Nonparametric Bayesian data analysis
• Bayesian analysis of mixture models with an unknown number of components\,--\,an alternative to reversible jump methods.
• Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
• Nonparametric Bayesian survival analysis using mixtures of Weibull distributions
• Bayesian Nonparametric Modeling Using Mixtures of Triangular Distributions
• Hierarchical Dirichlet Processes
• Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models
• A Predictive Approach to Model Selection
• Bayesian Analysis of Proportional Hazards Models Built from Monotone Functions
• Semiparametric Bayesian Analysis of Survival Data
• Bayesian Approach for Nonlinear Random Effects Models
• Adaptive Rejection Metropolis Sampling within Gibbs Sampling
• Semiparametric Regression
• Computational and Inferential Difficulties with Mixture Posterior Distributions
• Hierarchical Proportional Hazards Regression Models for Highly Stratified Data
• Bayesian Nonparametric Spatial Modeling With Dirichlet Process Mixing
• Bayesian survival analysis

This page was built for publication: Bayesian semiparametric modeling of survival data based on mixtures of \(B\)-spline distributions