63 citations · 531 across the 74 of their papers we have counts for
8 papers · 1 filter
A statistical machine learning approach for benchmarking in the presence of complex contextual factors and peer groups
Daniel W. Kennedy, Jessica Cameron, Paul P. -Y. Wu +1
The ability to compare between individuals or organisations fairly is important for the development of robust and meaningful quantitative benchmarks. To make fair comparisons, cont…
Peer groups for organisational learning: clustering with practical constraints
Daniel William Kennedy, Jessica Cameron, Paul Pao-Yen Wu +1
Peer-grouping is used in many sectors for organisational learning, policy implementation, and benchmarking. Clustering provides a statistical, data-driven method for constructing m…
Correcting misclassification errors in crowdsourced ecological data: A Bayesian perspective
Edgar Santos-Fernandez, Erin E. Peterson, Julie Vercelloni +2
Many research domains use data elicited from "citizen scientists" when a direct measure of a process is expensive or infeasible. However, participants may report incorrect estimate…
Bayesian Computation with Intractable Likelihoods
Matthew T. Moores, Anthony N. Pettitt, Kerrie Mengersen
This article surveys computational methods for posterior inference with intractable likelihoods, that is where the likelihood function is unavailable in closed form, or where evalu…
Bayesian item response models for citizen science ecological data
Edgar Santos-Fernandez, Kerrie Mengersen
So-called 'citizen science' data elicited from crowds has become increasingly popular in many fields including ecology. However, the quality of this information is being frequently…
Improved assessment of the accuracy of record linkage via an extended MaCSim approach
Shovanur Haque, Kerrie Mengersen
Record linkage is the process of bringing together the same entity from overlapping data sources while removing duplicates. Huge amounts of data are now being collected by public o…