Bayesian Estimation of Multinomial Cell Probabilities Incorporating Information from Aggregated Observations
Abstract
In this note, we consider the problem of estimating multinomial cell probabilities under the entropy loss when side information in aggregated data is available. We use the Jeffreys prior to obtain Bayes estimators. It is shown that by incorporating the side information, we can construct an improved estimator.
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