A big part of his work is figuring out when a statistical method is truly the best choice. Some problems have straightforward ...

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 ...

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 ...

Researchers have created a statistical method that may allow public health and infectious disease forecasters to better predict disease reemergence, especially for preventable childhood infections ...

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 ...

In a recent article published in the eLife Journal, researchers launched a possum excreta surveillance program across 350 km 2 in the Mornington Peninsula near South Melbourne, Australia. The study ...

A model is proposed for the study of plant breeding where the self-fertilization rate is of importance. The model can be used to provide convenient maximum likelihood estimation of the ...