7 citations · 19 across the 5 of their papers we have counts for
5 papers
Model updating after interventions paradoxically introduces bias
James Liley, Samuel R Emerson, Bilal A Mateen +3
Machine learning is increasingly being used to generate prediction models for use in a number of real-world settings, from credit risk assessment to clinical decision support. Rece…
Design choices for productive, secure, data-intensive research at scale in the cloud
Diego Arenas, Jon Atkins, Claire Austin +22
We present a policy and process framework for secure environments for productive data science research projects at scale, by combining prevailing data security threat and risk prof…
Shrinkage estimation of large covariance matrices using multiple shrinkage targets
Harry Gray, Gwenaël G. R. Leday, Catalina A. Vallejos +1
Linear shrinkage estimators of a covariance matrix --- defined by a weighted average of the sample covariance matrix and a pre-specified shrinkage target matrix --- are popular whe…
Bayesian Survival Modelling of University Outcomes
Catalina A. Vallejos, Mark F. J. Steel
The aim of this paper is to model the length of registration at university and its associated academic outcome for undergraduate students at the Pontificia Universidad Católica de…
On posterior propriety for the Student- linear regression model under Jeffreys priors
Catalina A. Vallejos, Mark F. J. Steel
Regression models with fat-tailed error terms are an increasingly popular choice to obtain more robust inference to the presence of outlying observations. This article focuses on B…