I recently provided advice on the precision to be expected from a trial of a new method of luring mammalian pests (feral cats, possums, and stoats, for example), to be carried out in Hikaroroa Reserve, near Karitane, NZ. This work was carried out for Thomas Hayward of Mammalian Corrections Unit (Dunedin, NZ), and was valuableContinue reading “Power Analysis for a new Method of Trapping Mammalian Pests”
I am delighted to be part of the five-year research project “Te Weu o te Kaitiaki – Indigenous Regeneration Pathways” that has just been funded by the Aotearoa New Zealand government. The proposal for this research was co-led led by Phil Lyver and Johanna Yletyinen of Manaaki Whenua (Landcare Research). It will use te aoContinue reading “New Project with Manaaki Whenua (Landcare Research)”
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 confidenceContinue reading “Online Course on Model Averaging”
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 recently provided advice on the use of “single-fit” bootstrapping to obtain confidence intervals for indices of relative abundance, when fitting a delta-lognormal model to fisheries data. The key idea is that of resampling the model parameters from a multivariate normal distribution. This is computationally nice as it allows a parametric bootstrap confidence interval toContinue reading “Faster bootstrap intervals for indices of relative abundance”
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 forContinue reading “Estimating percentiles in air dispersion modelling”
I am currently working with David Bryant at Otago University on testing lack-of-fit of a model in phylogenetics. It’s great to be able to use my research experience in estimating overdispersion on an important scientific problem. One of the key aspects of the problem is the sparseness in the data, which are multinomial with aContinue reading “Testing lack-of-fit in phylogenetics”
It’s been great to have these two papers come out in the last couple of weeks: Model-averaged confidence distributions: https://link.springer.com/article/10.1007/s10651-019-00432-5 Estimating overdispersion in sparse multinomial data:https://onlinelibrary.wiley.com/doi/10.1111/biom.13194