Joint Bayesian analysis of multiple response-types using the hierarchical generalized transformation model
DOI10.1214/20-ba1246OpenAlexW3102666008MaRDI QIDQ6121614
Publication date: 27 February 2024
Published in: Bayesian Analysis (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/journals/bayesian-analysis/volume-17/issue-1/Joint-Bayesian-Analysis-of-Multiple-Response-Types-Using-the-Hierarchical/10.1214/20-BA1246.full
Markov chain Monte CarlononlinearGibbs samplerBayesian hierarchical modelbig datalog-linear modelsnon-Gaussianmultiple response-types
Directional data; spatial statistics (62H11) Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15)
Cites Work
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- BART: Bayesian additive regression trees
- Two simple examples for understanding posterior \(p\)-values whose distributions are far from unform
- Multilevel latent Gaussian process model for mixed discrete and continuous multivariate response data
- Transformations and Bayesian density estimation
- Copula Gaussian graphical models and their application to modeling functional disability data
- Regularized rank-based estimation of high-dimensional nonparanormal graphical models
- Convex multi-task feature learning
- Multivariate adaptive regression splines
- Conjugate priors for exponential families
- Slice sampling. (With discussions and rejoinder)
- Objective Bayesian transformation and variable selection using default Bayes factors
- Computationally efficient multivariate spatio-temporal models for high-dimensional count-valued data (with discussion)
- Stable graphical model estimation with random forests for discrete, continuous, and mixed variables
- Posterior predictive \(p\)-values
- Smoothing methods in statistics
- High-dimensional semiparametric Gaussian copula graphical models
- Bayesian binomial mixture models for estimating abundance in ecological monitoring studies
- A new family of power transformations to improve normality or symmetry
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- Bayesian Inference for the Spatial Random Effects Model
- An Introduction to Categorical Data Analysis
- Bayesian transformation family selection: Moving toward a transformed Gaussian universe
- Fixed Rank Kriging for Very Large Spatial Data Sets
- Test of Significance for 2 × 2 Contingency Tables
- Estimating Optimal Transformations for Multiple Regression and Correlation
- Gibbs Sampling for Bayesian Non-Conjugate and Hierarchical Models by Using Auxiliary Variables
- Latent Variable Analysis of Multivariate Spatial Data
- Gibbs Sampling
- Bayesian Regression Tree Ensembles that Adapt to Smoothness and Sparsity
- Multivariate output analysis for Markov chain Monte Carlo
- Dimension Reduction and Alleviation of Confounding for Spatial Generalized Linear Mixed Models
- Bayesian Hierarchical Models With Conjugate Full-Conditional Distributions for Dependent Data From the Natural Exponential Family
- Hierarchical Models for Spatial Data with Errors that are Correlated with the Latent Process
- The continuity correction
- Causal Inference Using Potential Outcomes
- A likelihood analysis of quantile-matching transformations
- Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)
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