Gaussian distribution of known covariance s

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Suppose we have training data from the Gaussian distribution of known covariance S but unknown mean Mu. Suppose further that this mean itself is random, and characterized by Gaussian density having mean Mu0 and covariance S0. Explain the MAP (maximum a posteriori) estimator for the Mu?

Reference no: EM1320677

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