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

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 ...

Discover how predictive analytics uses data-driven models like decision trees and neural networks to forecast outcomes and ...

There are several books in the extensive and varied literature on Turbulence that deal, in statistical terms and in the context of fluid dynamics, with the phenomenon itself, as well as its many ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

There is a persistent belief in the ‘AI’ community that large language models (LLMs) have the ability to learn and self-improve by tweaking the weights in their vector space. Although ...

The feedback loops that define DeFi, on-chain contagion, and crypto financial crime are not statistical phenomena. They are causal ones. The industry's modelling infrastructure has not caught up. On 9 ...