Duquesne University大学的Bayesian Hierarchical Models资料，
当然，
作者，Steve Bronder，Department of Economics, Duquesne University,
一如既往的附有R代码。

主要内容：
The purpose of this documentation is to present a practical understanding and
implimentation of a Bayesian Hierarchical model. Bayesian Hierarchical models allow analysts to account
for endogeneity. A Bayesian Hierarchical model is a Bayesian network, a probabilistic graphical model that
represents a set of random variables and their conditional dependencies via a directed acyclic graph . Bayesian
Hierarchical models subset themselves by containing three or more levels of random variables or use latent
variables. One level uses within-unit analysis and another level for across-unit analysis. Within-unit model de-
scribes individual respondents over time.