Posterior propriety of an objective prior for generalized hierarchical normal linear models
Posterior propriety of an objective prior for generalized hierarchical normal linear models
Bayesian Hierarchical models has been widely used in modern statistical application. To deal with the data having complex structures, we propose a generalized hierarchical normal linear (GHNL) model which accommodates arbitrarily many levels, usual design matrices and 'vanilla' covariance matrices. Objective hyperpriors can be employed for the GHNL model to …