Sequential importance sampling for nonparametric Bayes models: The next generation

From MaRDI portal
Publication:4267407

DOI10.2307/3315637zbMath0957.62068OpenAlexW1974600023MaRDI QIDQ4267407

Merlise A. Clyde, Steven N. MacEachern, Jun S. Liu

Publication date: 19 December 1999

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/2d6bc1dac0a42e4d0affb32f548770186a6a92f5



Related Items

Conjugate analysis of multivariate normal data with incomplete observations, Bayesian nonparametric clustering as a community detection problem, Nonlinear and non-gaussian state estimation: A quasi-optimal estimator, A multi-resolution, non-parametric, Bayesian framework for identification of spatially-varying model parameters, Design of complex systems in the presence of large uncertainties: a statistical approach, Clustering Gene Expression Data using a Posterior Split-Merge-Birth Procedure, Online Bayesian learning for mixtures of spatial spline regressions with mixed effects, State Space Modeling & Bayesian Inference with Computational Intelligence, Usage of a pair of \(\mathbf S\)-paths in Bayesian estimation of a unimodal density, A PRticle filter algorithm for nonparametric estimation of multivariate mixing distributions, Iterative updating of model error for Bayesian inversion, Model-based structural health monitoring of naval ship hulls, Theory and computations for the Dirichlet process and related models: an overview, Sequential Monte Carlo methods for mixtures with normalized random measures with independent increments priors, Particle filters and Bayesian inference in financial econometrics, An improved collapsed Gibbs sampler for Dirichlet process mixing models, Gamma shape mixtures for heavy-tailed distributions, Nonparametric Bayesian data analysis, A predictive view of Bayesian clustering, The Ornstein-Uhlenbeck Dirichlet process and other time-varying processes for Bayesian nonparametric inference, Some issues in nonparametric Bayesian modeling using species sampling models, A flexible approach for multivariate mixed-effects models with non-ignorable missing values, A Dirichlet process mixture model for non-ignorable dropout, Multiple Imputation for Missing Values through Conditional Semiparametric Odds Ratio Models, Geometric sensitivity measures for Bayesian nonparametric density estimation models, Dirichlet process and its developments: a survey, Bayesian nonparametric clustering for large data sets, Nonparametric hierarchical Bayes analysis of binomial data via Bernstein polynomial priors



Cites Work