In this paper, we obtain explicit form of the posterior moments and characteristic functional for normalized random measures with independent increments (NRMIs) in terms of their associated Levy intensities, which is a class of Bayesian nonparametric priors that have been studied widely in the literature. These results are applied to solve the posterior consistency problem, the results of which are illustrated with examples.
翻译:在本文中,我们获得了明确的事后时刻形式,并获得了具有独立递增(NRMIs)的正常随机措施的功能特征,即相关的利维强度(Levy environments),这是在文献中广泛研究的一类巴耶斯非参数前科,这些结果被用于解决后科一致性问题,其结果以实例说明。