The estimation of large covariance and precision matrices is fundamental in modern
multivariate analysis. However, problems arise from the statistical analysis of large panel …

RA Fisher, the father of modern statistics, proposed the idea of fiducial inference during the
first half of the 20th century. While his proposal led to interesting methods for quantifying …

In recent years, a large variety of textbooks dealing with time-to-event analysis has been
published. Most of these books focus on the statistical analysis of observations in continuous …

In this paper we comprehensively survey the concept and strategies for building a resilient
and integrated cyber–physical system (CPS). Here resilience refers to a 3S-oriented design …

Support recovery of sparse signals from noisy measurements with orthogonal matching
pursuit (OMP) has been extensively studied. In this paper, we show that for any K-sparse …

We have collected and cleaned two network data sets: Coauthorship and Citation networks
for statisticians. The data sets are based on all research papers published in four of the top …

Statistical inference problems arising within signal processing, data mining, and machine
learning naturally give rise to hard combinatorial optimization problems. These problems …

SLOPE is adaptive to unknown sparsity and asymptotically minimax Page 1 The Annals of
Statistics 2016, Vol. 44, No. 3, 1038–1068 DOI: 10.1214/15-AOS1397 © Institute of …

Variable selection is a challenging issue in statistical applications when the number of
predictors p far exceeds the number of observations n. In this ultrahigh dimensional setting …

We consider estimation and inference in panel data models with additive unobserved
individual specific heterogeneity in a high-dimensional setting. The setting allows the …