Assessing Multinomial Distributions with a Bayesian Approach

This paper introduces a unified Bayesian approach for testing various hypotheses related to multinomial distributions. The method calculates the Kullback-Leibler divergence between two specified multinomial distributions, followed by comparing the change in distance from the prior to the posterior through the relative belief ratio. A prior elicitation algorithm is used to specify the prior distributions. To demonstrate the effectiveness and practical application of this approach, it has been applied to several examples.