Jim E. Griffin’s Research Page
Bayesian Nonparametric Methods, Regression Modelling with High-Dimensional Data, Time Series Modelling in Econometrics and Finance
- Bayesian Nonparametric Modelling of Macroeconomic Data - This is a joint project with Maria Kalli looking into flexible modelling of macroeconomic time series.
- Athletic Performance Passport - This is a joint project with James Hopker on developing methods for identifying unusual changes in the performance of elite athletes can be used to inform drug-testing programmes.
- Statistical Modelling of Environmental DNA (eDNA) - This is a joint project with Eleni Matechou. We have recently worked on Bayesian variable selection for model with false positives and false negative which can be used with single species eDNA data. We are extending this approach to multiple species metabarcoding data using joint species distribution models.
- Efficient Computational Methods for Bayesian Variable Selection. This work involves Mark Steel, Krys Latuszynski and Sam Livingstone. This work is looking at efficient computational methods for Bayesian variable selection in high-dimension problems and applications in areas such as genomics.
Some of my current and previous preprints are available from arXiv.org