Abstract
The paper considers the multivariate gamma distribution for which the method of moments has been considered as the only method of estimation due to the complexity of the likelihood function. With a non-conjugate prior, practical Bayesian analysis can be conducted using Gibbs sampling with data augmentation. The new methods are illustrated using artificial data for a trivariate gamma distribution as well as an application to technical inefficiency estimation.
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Tsionas, E.G. Bayesian inference for multivariate gamma distributions. Statistics and Computing 14, 223–233 (2004). https://doi.org/10.1023/B:STCO.0000035302.87186.be
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DOI: https://doi.org/10.1023/B:STCO.0000035302.87186.be