In this paper, we combine the time-varying financial network model and FARM-selection
approach to analyze the tail risk contagion between international financial market during the …

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

This article provides a selective overview of the recent developments in factor models and
their applications in econometric learning. We focus on the perspective of the low-rank …

This paper studies noisy low-rank matrix completion: given partial and noisy entries of a
large low-rank matrix, the goal is to estimate the underlying matrix faithfully and efficiently …

This article introduces a Factor Augmented Sparse Throughput (FAST) model that uses both
latent factors and sparse idiosyncratic components for nonparametric regression. It contains …

Bridging factor and sparse models Page 1 The Annals of Statistics 2023, Vol. 51, No. 4,
1692–1717 https://doi.org/10.1214/23-AOS2304 © Institute of Mathematical Statistics, 2023 …

This article proposes a model-free and data-adaptive feature screening method for ultrahigh-
dimensional data. The proposed method is based on the projection correlation which …

Factor models are a class of powerful statistical models that have been widely used to deal
with dependent measurements that arise frequently from various applications from genomics …

Abstract We propose the Factor Augmented (sparse linear) Regression Model (FARM) that
not only admits both the latent factor regression and sparse linear regression as special …

The evolution of green industrial policy in China is deeply embedded within a unique
political, economic, cultural, and social milieu. The intricacies and complexities inherent in …