Email Address: firstname.lastname@example.org
Other Research Theme Collaborations: ESH
I am a Senior Investigator Statistician working on Bayesian methods in precision medicine.
My current projects and interests include:
- Computationally-efficient, distributed methods in (generalised) evidence synthesis
- Flexible methods for modelling biomarkers
- Bayesian methods for weighted data
I am also interested in efficient computational methods for Bayesian inference, particularly in relation to model uncertainty and selection; dynamical systems; and graphical/DAG/network models.
I occasionally tweet.
Selected PapersGoudie, R. J. B., Presanis, A. M., Lunn, D., De Angelis, D., & Wernisch, L. (2018)Joining and splitting models with Markov melding
Bayesian Analysis : in press
Goudie, R. J. B., Turner, R. M., De Angelis, D., Thomas, A. (2017)Massively parallel MCMC for Bayesian hierarchical models
E-print : arXiv:1704.03216
Goudie, R. J. B., & Mukherjee, S. (2016)A Gibbs sampler for learning DAGs
Journal of Machine Learning Research 17: (30) 1–39
Goudie, R. J. B., Hovorka, R., Murphy, H. R., & Lunn, D. (2015)Rapid model exploration for complex hierarchical data: application to pharmacokinetics of insulin aspart
Statistics in Medicine 34: (23) 3144–3158
Goudie, R. J. B., Lunn, D., Hovorka, R., & Murphy, H. R. (2014)Pharmacokinetics of insulin aspart in pregnant women with type 1 diabetes: every day is different
Diabetes Care 37: (6) e121–e122