Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Bayesian quantile regression and statistical modelling represent a growing paradigm in contemporary data analysis, extending conventional regression by estimating various conditional quantiles rather ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Researchers have developed a new statistical model that predicts which cities are more likely to become infectious disease hotspots, based both on interconnectivity between cities and the idea that ...

The aim of this paper is to present some of the stylized features of financial data which have received a lot of attention both from practitioners and those with more theoretical backgrounds. Some of ...

A range of genetic factors can influence the onset of diseases like high blood pressure, heart disease, and type 2 diabetes, according to scientists. If we were to know how the DNA influences the risk ...

A new study published in the journal Science of The Total Environment has significant bearing on the hackneyed joke about chickens and their numerous reasons for crossing roads. In Florida, there's a ...

A statistical model -- now an easy-to-use software tool -- local police can use to identify a series of related crimes and nab a suspect has been unveiled. Crime linkage is the investigative process ...

Bracket Breakers is written by Peter Keating and Jordan Brenner. This series identified the major upsets in each region, using their Slingshot model, which was developed alongside the Furman ...