A new algorithm to generate beta processes

DOI10.1016/j.csda.2003.12.008zbMath1429.62023OpenAlexW2089857405MaRDI QIDQ957025

Yongdai Kim, Jaeyong Lee

Publication date: 26 November 2008

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

Full work available at URL: https://doi.org/10.1016/j.csda.2003.12.008

zbMATH Keywords

Markov chain Monte CarloLévy processbeta process

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Random number generation in numerical analysis (65C10)

Related Items

A Bernstein-von Mises theorem in the nonparametric right-censoring model, A mixture of beta-Dirichlet processes prior for Bayesian analysis of event history data, Lévy Adaptive B-spline Regression via Overcomplete Systems, The Bernstein-von Mises theorem for the proportional hazard model, On metrizing vague convergence of random measures with applications on Bayesian nonparametric models, On approximations of the beta process in latent feature models: point processes approach, Bayesian Analysis of the Proportional Hazards Model with Time‐Varying Coefficients, Bayesian Survival Analysis in Proportional Hazard Models with Logistic Relative Risk, Pricing Options Under a Generalized Markov-Modulated Jump-Diffusion Model, Non-parametric Bayesian analysis of clustered survival data, A Bayesian nonparametric goodness of fit test for right censored data based on approximate samples from the beta-Stacy process, Estimation of entropy and extropy based on right censored data: a Bayesian non-parametric approach

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonparametric Bayes estimators based on beta processes in models for life history data
• Bayesian analysis of proportional hazard models
• Tailfree and neutral random probabilities and their posterior distributions
• On posterior consistency of survival models
• Nonparametric Bayesian estimators for counting processes
• A Bayesian analysis of some nonparametric problems
• Adaptive Rejection Sampling for Gibbs Sampling
• Bayesian Inference for Generalized Linear and Proportional Hazards Models via Gibbs Sampling
• Bayesian survival estimation of Pareto distribution of the second kind based on failure-censored data.