Bayesian Analysis of the Independent Multi-Normal Process, Neither Mean Nor Precision Known (Classic Reprint) - Hardcover

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Excerpt from Bayesian Analysis of the Independent Multi-Normal Process, Neither Mean Nor Precision Known

We also show in section 3 that Bayesian joint inference-finding joint posterior and preposterior densities of the mean vector and the variance covariance matrix-is possible even when classical joint inference is not, i.s. When the number of objective sample observations is less than the number of distinct elements of the mean vector and variance-covariance matrix of the process.

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