- evgam v0.1.4 is now available on CRAN: https://CRAN.R-project.org/package=evgam
- A preprint on some of its uses is available on arXiv: arXiv:2003.04067
- If you're interested in a PhD on any of the topics below, do get in touch.
- Statistical modelling of extreme values and events
- Spatial statistics
- Natural hazards
- Parametric insurance
- Youngman, B. D. (2020). Flexible models for nonstationary dependence: Methodology and examples. In Revision.
arXiv:2001.06642 . - Youngman, B. D. (2020). evgam: An R package for Generalized Additive Extreme Value Models. Journal of Statistical Software. Accepted.
arXiv:2003.04067 . - Xiong X., Economou T. and Youngman B. D. (2020) Data fusion with Gaussian processes for estimation of environmental hazard events. Environmetrics. 2020;e2660.
DOI: 10.1002/env.2660 . To Appear. - Youngman, B. D. (2019). Generalized additive models for exceedances of high thresholds with an application to return level estimation for US wind gusts. Journal of the American Statistical Association 114(528), 1865–1879
DOI: 10.1080/01621459.2018.1529596 . - Figueiredo, R., M. L. Martina, D. B. Stephenson, and B. D. Youngman (2018). A probabilistic paradigm for the parametric insurance of natural hazards. Risk Analysis 38(11), 2400–2414.
DOI: 10.1111/risa.13122 . - Khare, S., Z. Chalabi, and B. Youngman (2018). Spatio-temporal distribution of historical extreme winter temperatures in England and Scotland |
a non-stationary extreme value analysis. Journal of Extreme Events 05 (01), 1750005.
DOI: 10.1142/S2345737617500051 . - Oakley, J. E. and B. D. Youngman (2017). Calibration of stochastic computer simulators using likelihood emulation. Technometrics 59 (1), 80-92.
DOI: 10.1080/00401706.2015.1125391 . - Youngman, B. D. and T. Economou (2017). Generalised additive point process
models for natural hazard occurrence. Environmetrics 28 (4), e2444.
DOI: 10.1002/env.2444 . - Stephenson, D. B., A. Hunter, B. Youngman, and I. Cook (2017). Chapter 3 -towards a more dynamical paradigm for natural catastrophe risk modeling. In G. Michel (Ed.), Risk Modeling for Hazards and Disasters, pp. 63-77. Elsevier.
DOI: 10.1016/C2015-0-01065-6 . - Youngman, B. D. and D. B. Stephenson (2016). A geostatistical extreme-value
framework for fast simulation of natural hazard events. Proceedings
of the Royal Society of London A: Mathematical, Physical and
Engineering Sciences 472 (2189).
DOI: 10.1098/rspa.2015.0855 - Roberts,
J., A. Champion, L. Dawkins, K. Hodges, L. Shaffrey, D. Stephenson,
M. Stringer, H. Thornton, and B. Youngman (2014). The XWS open
access catalogue of extreme European windstorms from 1979 to 2012.
Nat. Hazards Earth Syst. Sci 14, 2487-2501.
DOI: 10.5194/nhess-14-2487-2014 evgam
I have created the evgam R package for generalised additive extreme-value models. It's currently under development, but source code is provided with some examples.
ppgam
Theo Economou and I developed similar - yet slightly more basic - R code for generalised additive point process models, which accompanies Youngman and Economou (2017). Source code is provided with some examples.
recalibrate
This is a fairly simple R package for recalibrating spatial fields using observations and model output. The idea is that a spatial process has some true values that we want to infer from imperfect data. The code is motivated by, but generalises beyond, European windstorms.
contact details
Dr Benjamin D. Youngman
Lecturer
Statistical Science
College of Engineering, Mathematics and Physical Sciences
Laver Building
University of Exeter
Exeter, UK