Abstract
We investigate shrinkage methods for constructing predictive distributions. We consider the multivariate Normal model with a known covariance matrix and show that there exists a shrinkage predictive distribution dominating the Bayesian predictive distribution based on the vague prior when the dimension is not less than three. Kullback–Leibler divergence from the true distribution to a predictive distribution is adopted as a loss function.
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