8 citations · 17 across the 6 of their papers we have counts for
6 papers
A joint estimation approach for monotonic regression functions in general dimensions
Christian Rohrbeck, Deborah A Costain
Regression analysis under the assumption of monotonicity is a well-studied statistical problem and has been used in a wide range of applications. However, there remains a lack of a…
Some benefits of standardisation for conditional extremes
Christian Rohrbeck, Jonathan A Tawn
A key aspect where extreme values methods differ from standard statistical models is through having asymptotic theory to provide a theoretical justification for the nature of the m…
Simulating flood event sets using extremal principal components
Christian Rohrbeck, Daniel Cooley
Hazard event sets, a collection of synthetic extreme events over a given period, are important for catastrophe modelling. This paper addresses the issue of generating event sets of…
Bayesian non-parametric ordinal regression under a monotonicity constraint
Olli Saarela, Christian Rohrbeck, Elja Arjas
Compared to the nominal scale, the ordinal scale for a categorical outcome variable has the property of making a monotonicity assumption for the covariate effects meaningful. This…
Bayesian spatial clustering of extremal behaviour for hydrological variables
Christian Rohrbeck, Jonathan A Tawn
To address the need for efficient inference for a range of hydrological extreme value problems, spatial pooling of information is the standard approach for marginal tail estimation…
Bayesian Spatial Monotonic Multiple Regression
Christian Rohrbeck, Deborah Costain, Arnoldo Frigessi
We consider monotonic, multiple regression for a set of contiguous regions (lattice data). The regression functions permissibly vary between regions and exhibit geographical struct…