Randomly Generated LWF Chain Graphs

该数据集包含了随机生成的LWF链图，用于评估所提出类似PC算法的性能，并将其与LCD算法进行比较。该数据集基于顶点集合和每个顶点的平均边度生成。研究结果基于补充材料中的R语言实现。数据集涵盖了低维（50个变量，样本量为200和2000）以及高维（300个变量，样本量为100、200和300）的规模。任务是对链图学习算法的性能进行评估。

This dataset contains randomly generated LWF chain graphs, which are employed to assess the performance of the proposed PC-like algorithm and conduct a comparison with the LCD algorithm. This dataset is constructed based on the vertex set and the average edge degree per vertex. The research results are derived from the R implementation provided in the supplementary materials. This dataset includes both low-dimensional and high-dimensional scales: low-dimensional cases have 50 variables with sample sizes of 200 and 2000, while high-dimensional cases have 300 variables with sample sizes of 100, 200, and 300. The primary objective of this dataset is to evaluate the performance of chain graph learning algorithms.