We introduce a theoretical framework of elicitability and identifiability of set-valued
functionals, such as quantiles, prediction intervals, and systemic risk measures. A functional …

Many real-world processes are trajectories that may be regarded as continuous-time"
functional data". Examples include patients' biomarker concentrations, environmental …

The phenomenon of population interference, where a treatment assigned to one
experimental unit affects another experimental unit's outcome, has received considerable …

Causal inference is one of the core areas of research in modern data science that allows
researchers to determine whether a specific intervention or treatment has an effect on an …

This dissertation consists of three essays, each one tackling issues related to"
identification''in the statistical methods used in public health research. In the context of …

Experimentation increasingly drives everyday decisions in modern life, as it is considered by
some to be the gold standard for determining cause and effect within any system. Digital …