To protect financial institutions from unexpected credit losses, during the monitoring phase of granted loans it is of primary importance to foresee any evidence of a contagion of liquidity distress across a network of firms. This term indicates a …
The use of statistical methods in sport analytics has gained a rapidly growing interest over the last decade, and nowadays is common practice. In particular, the interest in understanding and predicting an athlete’s performance throughout his/her …
In professional tennis, it is often acknowledged that the server has an initial advantage. Indeed, the majority of points are won by the server, making the serve one of the most important elements in this sport. In this paper, we focus on the role of …
A problem that is frequently encountered in many areas of scientific research is that of estimating the effect of a non-randomized binary intervention on an outcome of interest by using time series data on units that received the intervention …
Coordinate-based meta-analyses (CBMA) allow researchers to combine the results from multiple functional magnetic resonance imaging experiments with the goal of obtaining results that are more likely to generalize. However, the interpretation of CBMA …
The World Anti-doping Agency currently collates the results of all doping tests for athletes involved in elite sporting competition with the aim of improving the fight against doping. Existing anti-doping strategies involve either the direct …
Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are …
Neuroimaging meta-analysis is an area of growing interest in statistics. The special characteristics of neuroimaging data render classical meta-analysis methods inapplicable and therefore new methods have been developed. We review existing …
Gaussian process (GP) models are widely used to emulate propagation uncertainty in computer experiments. GP emulation sits comfortably within an analytically tractable Bayesian framework. Apart from propagating uncertainty of the input variables, a …
In studies involving functional data, it is commonly of interest to model the impact of predictors on the distribution of the curves, allowing flexible effects on not only the mean curve but also the distribution about the mean. Characterizing the …