[02011] Network models with truncated Poisson-Dirichlet process priors
Session Time & Room : 3E (Aug.23, 17:40-19:20) @E501
Type : Contributed Talk
Abstract : We introduce a Bayesian nonparametric network model based on the truncated Poisson-Dirichlet process prior. In our model, the sociability parameters of the nodes are sorted in descending order. This enables us to focus on the most popular nodes of the network. We will show the simulation algorithm and posterior inference method for this model. Numerical implementations will also be discussed based on simulated observations and real-world datasets.
