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

In the Big Data era, many scientific and engineering domains are producing massive data streams, with petabyte and exabyte scales becoming increasingly common. Besides the explosive growth in volume, ...

In this video from PyCon Australia, Rhydwyn McGuire from the The New South Wales Department of Health presents: Video: Fast, Beautiful and Easy Bayesian Modeling – Can You have it all? Bayesian models ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

Uncertainty quantification (UQ) is a field of study that focuses on understanding, modeling, and reducing uncertainties in computational models and real-world systems. It is widely used in engineering ...

As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data have been created and analyzed, and logistic regression models have been key to ...

Predicting Workplace Conflicts through Intersectional Analysis of Social Identities of Employees: A Multilevel Statistical Modelling Approach Workplace conflict remains a persistent challenge to ...