论文标题
学习LWF链图：独立算法的订单
Learning LWF Chain Graphs: an Order Independent Algorithm
论文作者
论文摘要
LWF链图结合了有向的无环图和无向图。我们提出了一种类似PC的算法，该算法在忠实的假设下找到链图的结构，以解决Studeny（1997）的拟议算法可扩展性问题。我们证明，我们的PC状算法取决于顺序，因为输出可以取决于给出变量的顺序。在高维设置中，这种订单依赖性可以非常明显。我们建议对PC状算法进行两种修改，以删除部分或所有这些订单依赖性。在多种环境下的模拟结果表明，与基于分解的方法相比，PC样算法的竞争性能（称为LCD算法），Ma等人提出。 （2008年）在低维度和高维设置中的性能改善。
LWF chain graphs combine directed acyclic graphs and undirected graphs. We present a PC-like algorithm that finds the structure of chain graphs under the faithfulness assumption to resolve the problem of scalability of the proposed algorithm by Studeny (1997). We prove that our PC-like algorithm is order dependent, in the sense that the output can depend on the order in which the variables are given. This order dependence can be very pronounced in high-dimensional settings. We propose two modifications of the PC-like algorithm that remove part or all of this order dependence. Simulation results under a variety of settings demonstrate the competitive performance of the PC-like algorithms in comparison with the decomposition-based method, called LCD algorithm, proposed by Ma et al. (2008) in low-dimensional settings and improved performance in high-dimensional settings.
