Bayesian inference for finite mixtures of univariate and multivariate skew-normal and skew-t distributions
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Publication:3305024
DOI10.1093/biostatistics/kxp062zbMath1437.62465OpenAlexW2098439089WikidataQ46390591 ScholiaQ46390591MaRDI QIDQ3305024
Saumyadipta Pyne, Sylvia Frühwirth-Schnatter
Publication date: 4 August 2020
Published in: Biostatistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1093/biostatistics/kxp062
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- Bayesian mixture modelling in geochronology via Markov chain Monte Carlo
- Bayesian density estimation using skew Student-\(t\)-normal mixtures
- On the posterior distribution of the number of components in a finite mixture
- Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
- Maximum likelihood estimation for multivariate skew normal mixture models
- Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques*
- Model-Based Clustering of Non-Gaussian Panel Data Based on Skew-tDistributions
- On the Unification of Families of Skew-normal Distributions
- Model-Based Gaussian and Non-Gaussian Clustering
- The multivariate skew-normal distribution
- Real-Parameter Evolutionary Monte Carlo With Applications to Bayesian Mixture Models
- Dealing With Label Switching in Mixture Models
- Computational and Inferential Difficulties with Mixture Posterior Distributions
- Distributions Generated by Perturbation of Symmetry with Emphasis on a Multivariate Skewt-Distribution
- Bayesian Measures of Model Complexity and Fit
- Markov chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models
- A general class of multivariate skew-elliptical distributions
- Deviance information criteria for missing data models