Boris Beranger is currently a research associate at UNSW Sydney. He received a PhD in Statistics jointly from Université Pierre and Marie Curie, Paris 6 and UNSW with a thesis entitled ``Modelling the dependence structure of multivariate and spatial extremes''. His research focus on the analysis of extremes with a particular interests in modelling extreme environmental events. He also has a strong interest in analysing challenging and complex datasets using symbolic data analysis. More information can be found on my webpage
Research Interests:
Big Data
Extreme value theory
Symbolic data analysis
Qualifications:
Ph.D. in Statistics, Université Pierre and Marie Curie, Paris 6, France and UNSW Sydney, Australia.
Publications
Invited talks, refereed proceedings and other conference outputs
Whitaker, T.., Beranger B.., & Sisson S.
(2017). A composite likelihood based approach for max-stable processes using histogram-valued variables. Extreme Value Analysis 2017.
Sisson, S., Beranger B.., Lin H.., & Whitaker T..
(2017). New methods for symbolic data analysis (conference presentation). SDA17 international conference, Ljubljana, Slovenia.
Beranger, B.., Padoan S.. A., Xu Y.., & Sisson S. A.
(2019). Extremal properties of the univariate extended skew-normal distribution. Statistics and Probability Letters. 147, 73-82.
Beranger, B.., Padoan S.. A., Xu Y.., & Sisson S. A.
(2019). Extremal properties of the multivariate extended skew-normal distribution. Statistics and Probability Letters. 147, 105-114.
Beranger, B.., Duong T.., Perkins-Kirkpatrick S.., & Sisson S. A.
(2019). Tail density estimation for exploratory data analysis using kernel methods. Journal of Nonparametric Statistics. 31, 144-174.
Beranger, B.., Padoan S.. A., & Sisson S.
(2017). Models for extremal dependence derived from skew-symmetric families.. Scandinavian Journal of Statistics. 44, doi: 10.1111/sjos.12240
