Individuals or companies in a large social or financial network often display rather
heterogeneous behaviors for various reasons. In this work, we propose a network vector …

In network analysis, how to estimate the number of communities K is a fundamental problem.
We consider a broad setting where we allow severe degree heterogeneity and a wide range …

Modeling responses on the nodes of a large-scale network is an important task that arises
commonly in practice. This paper proposes a community network vector autoregressive …

A two-mode network contains two types of nodes, and edges exist only between any two
nodes that are associated with different entities. Owing to the network connections (ie …

A high-order network model with explicit relationship, implicit relationship and hyper nodes
is constructed based on the characteristics of social networks. Based on this model, the …

With the development of the internet, network data with replications can be collected at
different time points. The spatial autoregressive panel (SARP) model is a useful tool for …

While the Vector Autoregression (VAR) model has received extensive attention for modelling
complex time series, quantile VAR analysis remains relatively underexplored for high …

Motivated by a dataset of burglaries in Chicago, USA, we introduce a novel framework to
analyze time series of count data combining common multivariate time series models with …

Owing to the rapid development of social networking sites, the spatial autoregressive (SAR)
model plays an important role in social network studies. However, the underlying structure of …

We propose a dynamic network quantile regression model to investigate the quantile
connectedness using a predetermined network information. We extend the existing network …