Rate My Professor Livingston Jr

Dr. Glen Livingston Jr is a Senior Lecturer in the School of Computer and Information Sciences at the University of Newcastle, Australia, within the Data Science and Statistics group of the College of Engineering, Science and Environment. He holds a Doctor of Philosophy in Statistics from the University of Newcastle, along with a Bachelor of Mathematics (Honours), a Bachelor of Commerce from the same institution, and a Graduate Diploma from the Institute of Chartered Accountants Australia. His academic interests focus on multivariate time series modelling, regime switching volatility models, simulation and computational statistics, and Bayesian estimation methods including Markov chain Monte Carlo. Livingston Jr specializes in Bayesian statistics, big time series, Cochran-Mantel-Haenszel tests, forecasting, MCMC algorithms, non-linear multivariate time series, and non-parametric statistics. His research contributions span statistical theory (20%), statistics not elsewhere classified (40%), and stochastic analysis and modelling (40%).

In his career at the University of Newcastle, Dr. Livingston Jr has co-authored the book 'An Introduction to Cochran-Mantel-Haenszel Testing and Nonparametric ANOVA' (2023, Wiley) with J.C.W. Rayner. Notable publications include 'Relating the Friedman test adjusted for ties, the Cochran-Mantel-Haenszel mean score test and the ANOVA F test' (Communications in Statistics-Theory and Methods, 2023), 'Bayesian inference for smooth transition autoregressive (STAR) model: A prior sensitivity analysis' (Communications in Statistics-Simulation and Computation, 2017), 'Component Analysis When Testing for Fixed Effects in Unbalanced ANOVAs' (Stats, 2025), 'Orthogonal contrasts for both balanced and unbalanced designs' (Statistica Neerlandica, 2024), and 'Comparing clustering approaches for smart meter time series' (Applied Energy, 2025). Additional works cover applications in sports performance analysis and electric shock probability modelling. His publications appear in journals such as Statistical Papers, Journal of Science and Medicine in Sport, and ACM Transactions on Knowledge Discovery from Data, reflecting interdisciplinary impact.