A Bayesian Nonparametric Test for Assessment of Normality
A Bayesian Nonparametric Test for Assessing Multivariate Normality
A novel nonparametric test for assessing multivariate normal models is presented.The proposed approach is based on the use of the use of the dirichletprocess and the mahalanobis distance.More precisely, the mahalanobis distance is employed as a good technique to transform the problem into a univariate problem.Then the dirichlet process is used as a prior on the distribution of the distribution of the distribution of the distribution of the distribution of the distance between the posterior process and the chi-square distribution with degrees of freedom via a relative belief ratio.The procedure is illustrated through several examples, in which the proposed approach shows excellent performance.
