Many research questions in Earth and environmental sciences are inherently causal,
requiring robust analyses to establish whether and how changes in one variable cause …

The usage of psychological networks that conceptualize behavior as a complex interplay of
psychological and other components has gained increasing popularity in various research …

There is considerable heterogeneity in immunological parameters between individuals, but
its sources are largely unknown. To assess the relative contribution of heritable versus non …

Predicting the dependencies between observations from multiple time series is critical for
applications such as anomaly detection, financial risk management, causal analysis, or …

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 …

Statistical models of text have become increasingly popular in statistics and computer
science as a method of exploring large document collections. Social scientists often want to …

This chapter demonstrates how the Ising model can be estimated. It shows that the Ising
model is equivalent to, or closely related to, prominent modeling techniques in …

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

The paper deals with the estimation of a high dimensional covariance with a conditional
sparsity structure and fast diverging eigenvalues. By assuming a sparse error covariance …

Importance Enhanced understanding of factors associated with symptomatic and functional
recovery is instrumental to designing personalized treatment plans for people with …