AbstractSystems-level analysis of an engineered structure demands robust scientific and statistical protocols to assess model-driven conclusions that are often nontraditional causal in their co...

Density forecasts of locally explosive processes are investigated using mixed causal-noncausal models, namely time series models with both lag and lead components. In the absence theoretical expressions for predictive density a large range potential error distributions, two approximation methods analysed compared Monte Carlo simulations. The focus is on prediction one-step ahead probabilities t...

In this paper we study methods for estimating causal effects in settings with panel data, where some units are exposed to a treatment during periods and the goal is counterfactual (untreated) outcomes treated unit/period combinations. We propose class of matrix completion estimators that uses observed elements control corresponding untreated unit/periods impute "missing" outcome matrix, units/p...

Mediation analysis aims at identifying and evaluating the mechanisms through which treatment affects an outcome. The goal is to disentangle total effect into two components: indirect that occurs due one or more intermediate variables, known as mediators, direct captures all other possible explanations for why a works. This paper reviews methodological advancements in literature on causal mediat...

We introduce a dense and dilute loop model on causal dynamical triangulations. Both models are characterised by geometric coupling constant $g$ parameter $\alpha$ in such way that the purely triangulation is recovered for $\alpha=1$. show can be mapped to solvable planar tree model, whose partition function we compute explicitly use determine critical behaviour of model. The likewise model; how...