Artificial intelligence can solve problems at remarkable speed, but it's the people developing the algorithms who are truly ...

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 ...

Surveillance data collected on several hundred different infectious organisms over 20 years have revealed striking power relationships between their variance and mean in successive time periods. Such ...

Throughout the years I have worked in credit and collections, either doing credit analysis related to commercial lending decisions or identifying the elements that should be weighed when reviewing ...

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 ...

Information on Earth's biodiversity is increasingly collected using DNA-, image- and audio-based sampling. At the same time, ...

Abstract: In this paper, firstly, flow duration curves (FDCs) for hydrological extremes were calibrated for a range of aggregation levels and seasons to provide compressed statistical information for ...