Existing high dimensional two-sample tests usually assume that different elements of a high dimensional predictor are weakly dependent. Such a condition can be violated when data follow a low dimensional latent factor structure. As a result, the recently developed two-sample testing methods are...

Nearest neighbor imputation (NNI) is a popular method used to compensate for item nonresponse in sample surveys. Although previous results showed that the NNI sample mean and quantiles are consistent estimators of the population mean and quantiles, large sample inference procedures, such as...

We propose a new class of spatio-temporal models with unknown and banded autoregressive coefficient matrices. The setting represents a sparse structure for high-dimensional spatial panel dynamic models when panel members represent economic (or other type) individuals at many different locations....

The complex tail dependency structure in a dynamic network with a large number of nodes is an important object to study. Here we propose a network quantile autoregression model (NQAR), which characterizes the dynamic quantile behavior. Our NQAR model consists of a system of equations, of which...