Dr Rob Deardon: Current Research
Interests
1.
Statistical modeling of infectious diseases.
·
diseases of humans, animals and plants
·
spatial systems
·
network-based systems
·
measurement error
·
robustness to
assumptions
·
computational
methodologies
·
study design
·
model comparison
·
model adequacy /
goodness of fit
2.
Bayesian and computational statistics.
·
Markov
chain Monte Carlo methods (MCMC)
·
importance sampling and sequential Monte Carlo (SMC)
·
approximate Bayesian computation (ABC)
3.
Statistical modeling of ecological systems.
4.
Experimental design.
·
crop trials (e.g.
dealing with inter-plot interference in experiments on crop diseases)
·
spatial design for
experiments used to ascertain disease dynamics
·
designs for Markov
chains
·
Bayesian experimental design
5.
Statistical
learning.
·
multivariate models
for spectral data (e.g. chemical composition of wine grapes)
·
high dimensional
model selection (e.g. gene selection)
·
predictive modeling of various systems