 
					Research Interests
Theory and Methods:
- ♦ Spatial Statistics
- ♦ Extreme Value Analysis
- ♦ Nonparametric Regression
- ♦ Probabilistic Forecasting
Applications:
- ♦ Environmental Science
- ♦ Finance and Insurance
- ♦ Health
Publications
						 
O'Toole, P, Rohrbeck, C & Richards, J (2025).  Clustering of multivariate tail dependence using conditional methods. 
    Journal Article.  Under review.
McGonigle, ET, Pawley, M, Richards, J & Rohrbeck, C (2025). 
 MOPED: A moving sum method for change point detection in pairwise extremal dependence.
						    Journal Article.  Under review.
						Rohrbeck, C & Costain, DA (2025).
						 A joint estimation approach for monotonic regression functions in general dimensions.
						    Journal Article.  Scandinavian Journal of Statistics, 52(2), 903-923.
Rohrbeck, C, Simpson, ES & Tawn, JA (2025).
						 Editorial: EVA (2023) conference data challenge.
						    Special issue editorial. Extremes, 28(1), 1-21.
						Rohrbeck, C & Tawn, JA (2024).
						 Some benefits of standardisation for conditional extremes.
						    Journal Article. Stat, 13(1), e647.
						Rohrbeck, C & Cooley, D (2023).
						 Simulating flood event sets using extremal principal components.
						    Journal Article. Annals of Applied Statistics, 17(2), 1333-1352.
						
						Saarela, O, Rohrbeck, C & Arjas, E (2023).
						 Bayesian non-parametric ordinal regression under a monotonicity constraint.
						    Journal Article. Bayesian Analysis, 18(1), 193-221.
 
						
						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.