Big Data bring new opportunities to modern society and challenges to data scientists. On the
one hand, Big Data hold great promises for discovering subtle population patterns and …

This article surveys work on a class of models, dynamic factor models (DFMs), that has
received considerable attention in the past decade because of their ability to model …

This chapter provides an overview of and user's guide to dynamic factor models (DFMs),
their estimation, and their uses in empirical macroeconomics. It also surveys recent …

This paper extends the Common Correlated Effects (CCE) approach developed by Pesaran
(2006) to heterogeneous panel data models with lagged dependent variables and/or weakly …

Researchers have adopted online data such as search engine query volumes to forecast
tourism demand for a destination, including tourist numbers and hotel occupancy. However …

This article provides an overview of the panel vector autoregressive models (VAR) used in
macroeconomics and finance to study the dynamic relationships between heterogeneous …

This article describes a large, monthly frequency, macroeconomic database with the goal of
establishing a convenient starting point for empirical analysis that requires “big data.” The …

The aim of this book is to investigate the spectral properties of random matrices (RM) when
their dimensions tend to infinity. All classical limiting theorems in statistics are under the …

Statistical Foundations of Data Science gives a thorough introduction to commonly used
statistical models, contemporary statistical machine learning techniques and algorithms …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …