论文标题
叶子附着的随机树生长
Growth of Random Trees by Leaf Attachment
论文作者
论文摘要
我们通过将新顶点的概率附着在叶子上的概率附着来研究一棵定期生根的树的生长。我们根据树的连通性构建叶子的可能性功能。我们采用这种连通性，以通过从叶到根到根的有序有序路径合并来诱导。将可能性与分配的先验分布相结合导致后叶分布，从中为新顶点采样附着点。我们提出了这种贝叶斯树生长的计算示例。尽管讨论是通用的，但本文的初始动机是分布式分类帐的概念，分布式分类帐的概念可以被视为按概率叶子附着生长的时间订购的随机树。
We study the growth of a time-ordered rooted tree by probabilistic attachment of new vertices to leaves. We construct a likelihood function of the leaves based on the connectivity of the tree. We take such connectivity to be induced by the merging of directed ordered paths from leaves to the root. Combining the likelihood with an assigned prior distribution leads to a posterior leaf distribution from which we sample attachment points for new vertices. We present computational examples of such Bayesian tree growth. Although the discussion is generic, the initial motivation for the paper is the concept of a distributed ledger, which may be regarded as a time-ordered random tree that grows by probabilistic leaf attachment.
