On Monte Carlo methods for Bayesian multivariate regression models with heavy-tailed errors
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- repec:bla:jfinan:v:44:y:1989:i:4:p:889-908 is not listed on IDEAS
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- Jung, Yeun Ji & Hobert, James P., 2014. "Spectral properties of MCMC algorithms for Bayesian linear regression with generalized hyperbolic errors," Statistics & Probability Letters, Elsevier, vol. 95(C), pages 92-100.
- Qin, Qian & Hobert, James P., 2018. "Trace-class Monte Carlo Markov chains for Bayesian multivariate linear regression with non-Gaussian errors," Journal of Multivariate Analysis, Elsevier, vol. 166(C), pages 335-345.
- Li, Haoxiang & Qin, Qian & Jones, Galin L., 2024. "Convergence analysis of data augmentation algorithms for Bayesian robust multivariate linear regression with incomplete data," Journal of Multivariate Analysis, Elsevier, vol. 202(C).
- Choi, Hee Min & Hobert, James P., 2013. "Analysis of MCMC algorithms for Bayesian linear regression with Laplace errors," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 32-40.
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Keywords
Data augmentation algorithm Drift condition Geometric ergodicity Markov chain Minorization condition Robust multivariate regression;Statistics
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