Bayesian semiparametric analysis for latent variable models with mixed continuous and ordinal outcomes
From MaRDI portal
Publication:530384
DOI10.1016/j.jkss.2016.01.005zbMath1342.62103OpenAlexW2260385411MaRDI QIDQ530384
Publication date: 29 July 2016
Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jkss.2016.01.005
blocked Gibbs samplermodel comparisonlatent variable modelfinite dimensional truncated stick-breaking prior
Factor analysis and principal components; correspondence analysis (62H25) Density estimation (62G07)
Related Items (3)
Bayesian analysis for mixture of latent variable hidden Markov models with multivariate longitudinal data ⋮ Bayesian semiparametric latent variable model with DP prior for joint analysis: Implementation with nimble ⋮ Dirichlet process and its developments: a survey
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Analysis of structural equation model with ignorable missing continuous and polytomous data
- On a class of Bayesian nonparametric estimates: I. Density estimates
- Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
- Consistency property of elliptical probability density functions
- Nonparametric Bayesian data analysis
- Bayesian nonparametric estimation for incomplete data via successive substitution sampling
- Maximum likelihood methods in treating outliers and symmetrically heavy-tailed distributions for nonlinear structural equation models with missing data
- A Bayesian analysis of some nonparametric problems
- Bayesian Tobit Modeling of Longitudinal Ordinal Clinical Trial Compliance Data With Nonignorable Missingness
- Marginal Likelihood from the Gibbs Output
- Maximum Likelihood Analysis of a General Latent Variable Model with Hierarchically Mixed Data
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- The Calculation of Posterior Distributions by Data Augmentation
- A semiparametric Bayesian model for randomised block designs
- Model choice: a minimum posterior predictive loss approach
- Estimating Normal Means with a Dirichlet Process Prior
- The Collapsed Gibbs Sampler in Bayesian Computations with Applications to a Gene Regulation Problem
- Reparameterizing the generalized linear model to accelerate gibbs sampler convergence
- Bayesian Tests and Model Diagnostics in Conditionally Independent Hierarchical Models
- Dirichlet Process Mixed Generalized Linear Models
- Dynamic Latent Trait Models for Multidimensional Longitudinal Data
- Marginal Likelihood and Bayes Factors for Dirichlet Process Mixture Models
- Markov chain Monte Carlo in approximate Dirichlet and beta two-parameter process hierarchical models
- Statistical Inference Based on Pseudo-Maximum Likelihood Estimators in Elliptical Populations
- Gibbs Sampling Methods for Stick-Breaking Priors
- Estimating normal means with a conjugate style dirichlet process prior
- Bayesian Density Estimation and Inference Using Mixtures
- Bayes Factors
- Latent Variable Models with Mixed Continuous and Polytomous Data
- Equation of State Calculations by Fast Computing Machines
- Nonparametric Priors for Ordinal Bayesian Social Science Models: Specification and Estimation
- Bayesian Analysis of Binary and Polychotomous Response Data
- Monte Carlo sampling methods using Markov chains and their applications
- Structural Equation Modeling
This page was built for publication: Bayesian semiparametric analysis for latent variable models with mixed continuous and ordinal outcomes
