Statistical Network Analysis: Estimation and Inference
Abstract: Recent advances in computing and measurement technologies have led to an explosion in the amount of data with network structures in a variety of…
Abstract: Recent advances in computing and measurement technologies have led to an explosion in the amount of data with network structures in a variety of…
Abstract: Estimating dynamic treatment effects is essential across various disciplines, offering nuanced insights into the time-dependent causal impact of interventions. However, this estimation presents challenges…
Abstract: Respondent-driven sampling (RDS) is a network-based sampling strategy used to study hidden populations for which no sampling frame is available. In each epoch of…
Abstract: While right-censored time-to-event outcomes have been studied for decades, handling time-to-event covariates, also known as censored covariates, is now of growing interest. So far,…
Abstract: Graphs and networks are widely used to represent complex systems such as genetic regulatory networks, brain connectivity networks, etc. Learning underlying graphs from high-dimensional…