23 citations · 32 across the 8 of their papers we have counts for
8 papers
Mathematical modelling and uncertainty quantification for analysis of biphasic coral reef recovery patterns
David J. Warne, Kerryn Crossman, Grace E. M. Heron +6
Coral reefs are increasingly subjected to major disturbances threatening the health of marine ecosystems. Substantial research underway to develop intervention strategies that assi…
Optimal Clustering with Dependent Costs in Bayesian Networks
Paul Pao-Yen Wu, Fabrizio Ruggeri, Kerrie Mengersen
Background: Clustering of nodes in Bayesian Networks (BNs) and related graphical models such as Dynamic BNs (DBNs) has been demonstrated to enhance computational efficiency and imp…
clusterBMA: Bayesian model averaging for clustering
Owen Forbes, Edgar Santos-Fernandez, Paul Pao-Yen Wu +7
Various methods have been developed to combine inference across multiple sets of results for unsupervised clustering, within the ensemble clustering literature. The approach of rep…
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…
Combined parameter and state inference with automatically calibrated ABC
Anthony Ebert, Pierre Pudlo, Kerrie Mengersen +2
State space models contain time-indexed parameters, termed states, as well as static parameters, simply termed parameters. The problem of inferring both static parameters as well a…
Likelihood-free parameter estimation for dynamic queueing networks: case study of passenger flow in an international airport terminal
Anthony Ebert, Ritabrata Dutta, Kerrie Mengersen +3
Dynamic queueing networks (DQN) model queueing systems where demand varies strongly with time, such as airport terminals. With rapidly rising global air passenger traffic placing i…
Computationally Efficient Simulation of Queues: The R Package queuecomputer
Anthony Ebert, Paul Wu, Kerrie Mengersen +1
Large networks of queueing systems model important real-world systems such as MapReduce clusters, web-servers, hospitals, call centers and airport passenger terminals. To model suc…