作者：Crane, Harry; Xu, Min
作者单位：Rutgers University System; Rutgers University New Brunswick
摘要：The spread of infectious disease in a human community or the proliferation of fake news on social media can be modelled as a randomly growing tree-shaped graph. The history of the random growth process is often unobserved but contains important information such as the source of the infection. We consider the problem of statistical inference on aspects of the latent history using only a single snapshot of the final tree. Our approach is to apply random labels to the observed unlabelled tree and...
