Research Interests

Theory and Methods:

  • ♦ Spatial Statistics
  • ♦ Extreme Value Theory
  • ♦ Nonparametric Regression
  • ♦ Probabilistic Forecasting

Applications:

  • ♦ Environmental Sciences and Meteorology
  • ♦ Finance and Insurance

Publications

Rohrbeck, C & Tawn, JA (2022). Standardisation overcomes counter-examples of conditional extremes.
    Journal Article. Submitted.
Rohrbeck, C & Cooley, D (2022). Simulating flood event sets using extremal principal components.
    Journal Article. Accepted for Annals of Applied Statistics.
Saarela, O, Rohrbeck, C & Arjas, E (2022). Bayesian non-parametric ordinal regression under a monotonicity constraint.
    Journal Article. Accepted for Bayesian Analysis.
Rohrbeck, C, Simpson, ES & Towe, RP (2021). A spatio-temporal model for Red Sea surface temperature anomalies.
    Journal Article. Extremes, 24(1), 129-144.
Rohrbeck, C & Tawn, JA (2021). Bayesian spatial clustering of extremal behaviour for hydrological variables .
    Journal Article. Journal of Computational and Graphical Statistics, 30(1), 91-105.
Barlow, AM, Rohrbeck, C, Sharkey, P, Shooter, R & Simpson, ES (2018). A Bayesian spatio-temporal model for precipitation extremes - STOR team contribution to the EVA2017 challenge.
    Journal Article. Extremes, 21(3), 431-439.
Rohrbeck, C, Costain, DA & Frigessi, A (2018). Bayesian spatial monotonic multiple regression.
    Journal Article. Biometrika, 105(3), 691-707.
Rohrbeck, C, Eastoe, EF, Frigessi, A & Tawn, JA (2018). Extreme value modelling of water-related insurance claims.
    Journal Article. Annals of Applied Statistics, 12 (1), 246-282.
Rohrbeck, C (2016). Statistical Methods for Weather-related Insurance Claims.
   Doctoral Thesis. Lancaster University. 216 p.
Rohrbeck, C (2012). Combining Probabilistic Forecasts by Isotonic Recursive Partitioning.
   Diplomarbeit. Heidelberg University. 91 p.