论文标题
最小信息依赖建模
Minimum information dependence modeling
论文作者
论文摘要
我们提出了一种构建混合域数据的联合统计模型以分析其依赖性的方法。多元高斯和对数线性模型是所提出模型的特定示例。结果表明，定义模型的功能方程在相当弱的条件下具有独特的解决方案。该模型的特征是两个正交参数：依赖性参数和边缘参数。为了估计依赖性参数，提出了条件推理以及采样过程，并显示出提供一致的估计量。提出了涉及企鹅和地震的数据分析的说明性示例。
We propose a method to construct a joint statistical model for mixed-domain data to analyze their dependence. Multivariate Gaussian and log-linear models are particular examples of the proposed model. It is shown that the functional equation defining the model has a unique solution under fairly weak conditions. The model is characterized by two orthogonal parameters: the dependence parameter and the marginal parameter. To estimate the dependence parameter, a conditional inference together with a sampling procedure is proposed and is shown to provide a consistent estimator. Illustrative examples of data analyses involving penguins and earthquakes are presented.
