Graphical modelling is an important branch of statistics that has been successfully applied in
biology, social science, causal inference and so on. Graphical models illuminate …

This study relates sea surface temperature (SST) to the upwelling conditions off the
southwest coast of Portugal using statistical analyses of publically available data. Optimum …

Neuroimaging is the growing area of neuroscience devoted to produce data with the goal of
capturing processes and dynamics of the human brain. We consider the problem of inferring …

Despite the large research effort devoted to learning dependencies between time series, the
state of the art still faces a major limitation: existing methods learn partial correlations but fail …

Suppose that we have a historical time series with samples taken at a slow rate, eg
quarterly. The paper proposes a new method to answer the question: is it worth sampling the …

Offsite construction (OSC) transfers onsite construction activities to factory-based processes
utilising technological advancements, resulting in new and emerging skills while causing …

High-dimensional multivariate time series are challenging due to the dependent and high-
dimensional nature of the data, but in many applications there is additional structure that can …

Graphical time series models encode the conditional independence among the variables of
a multivariate time series. An iterative method is proposed to estimate a graphical time …

Identifying the interaction of air pollutants in each monitoring station and the inter‐
relationship between pollutants at different stations is an important issue in the management …

Discrete-time ARMA processes can be placed in a one-to-one correspondence with a set of
continuous-time processes that are bounded in frequency by the Nyquist value of π radians …