What Does Objective Mean in a Dirichlet‐multinomial Process?
研究了在类别数较多时，如何为狄利克雷-多项过程选择客观先验分布，并比较了不同先验对后验分布的影响，帮助学者判断哪种先验更合理。
Summary The Dirichlet‐multinomial process can be seen as the generalisation of the binomial model with beta prior distribution when the number of categories is larger than two. In such a scenario, setting informative prior distributions when the number of categories is great becomes difficult, so the need for an objective approach arises. However, what does objective mean in the Dirichlet‐multinomial process? To deal with this question, we study the sensitivity of the posterior distribution to the choice of an objective Dirichlet prior from those presented in the available literature. We illustrate the impact of the selection of the prior distribution in several scenarios and discuss the most sensible ones.