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 & Costain, DA (2023).
A joint estimation approach for monotonic regression functions in general dimensions.
Journal Article. Submitted.
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.