可分解离散图模型的替代参数化和参考先验
Alternative parametrizations and reference priors for decomposable discrete graphical models
摘要：
对于一个给定的离散可分解的图形模型，我们确定了几个替代的参数化，并构造相应的参考先验的参数的适当分组。具体地说，假设图的团是安排在一个完美的顺序，我们考虑的参数是条件概率的candle-残差给定的分隔符，以及广义对数优势比。我们还考虑了与代表统计模型的切割的变量集合相关联的参数化。我们得到的参考先验不依赖于分组的顺序，属于共轭族，并且是适当的。
英文摘要：
For a given discrete decomposable graphical model, we identify several alternative parametrizations, and construct the corresponding reference priors for suitable groupings of the parameters. Specifically, assuming that the cliques of the graph are arranged in a perfect order, the parameters we consider are conditional probabilities of clique-residuals given separators, as well as generalized log-odds-ratios. We also consider a parametrization associated to a collection of variables representing a cut for the statistical model. The reference priors we obtain do not depend on the order of the groupings, belong to a conjugate family, and are proper.
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