Bayesian inference in a matrix normal dynamic linear model with unknown covariance matrices

DOI10.1080/02331880410001692985zbMath1057.62023OpenAlexW2046035021MaRDI QIDQ4659551

Jose Luis Gallizo, Pilar Gargallo, Manuel Salvador

Publication date: 21 March 2005

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331880410001692985

zbMATH Keywords

Gibbs samplingmatrix normaldynamic principal componentsmultivariate betaMNDLM

Mathematics Subject Classification ID

Related Items (3)

Multivariate stochastic volatility with Bayesian dynamic linear models ⋮ Bound and convergence of the non-constant dynamic linear model ⋮ Posterior mean and variance approximation for regression and time series problems

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• DATA AUGMENTATION AND DYNAMIC LINEAR MODELS
• On Gibbs sampling for state space models
• Bayesian Vector Autoregressions with Stochastic Volatility
• Marginal Likelihood From the Metropolis–Hastings Output

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