There is now an online course to go with my book on model averaging. This course provides an up-to date overview of the topic, from both the Bayesian and frequentist perspective, including methods that are popular in machine learning, such as bagging and stacking. Recent developments, published since the book came out in 2018, are also covered, including confidence distributions, the frequentist analogue of posterior distributions. There is emphasis on understanding the theory underlying the methods and on experience using the methods in RStudio.

Cost: US$200 (+ applicable taxes) for 30 days access. You can find more information and registration details here

I have recently been providing advice to Mark Herse, a PhD student at the University of Canterbury, on statistical issues relating to population modelling of black swans.

I am looking forward to collaborating with Darryl MacKenzie and Stefan Meyer of Proteus Wildlife Research Consultants early next year on a project funded by the New Zealand Ministry of Primary Industries looking at the risk from fisheries bycatch to marine mammal species.

I am delighted to be working with James Reardon from the NZ Department of Conservation on a project concerned with sustainable mouse control. It will be good to get into the design and statistical modelling issues in this study.

I have recently been providing advice to STIMBR (Stakeholders in Methyl Bromide Reduction) on the estimation of percentiles when modelling the dispersion of chemicals in the atmosphere. It was interesting to see just how unreliably the highest upper percentiles of a skewed distribution are estimated, even from a very large sample. This has implications for the use of such percentiles in setting environmental health regulations.