Ensemble prediction systems aim to account for uncertainties of initial conditions and model error. Ensemble forecasting is sometimes viewed as a method of obtaining (objective) probabilistic forecasts. How is one to judge the quality of an ensemble at forecasting a system? The probability that...

Quantitative modeling of risk and hazard from flooding involves decisions regarding the choice of model and goal of the modeling exercise, expressed by some measure of performance. This paper shows how the subjectivity in the choices of performance measures and observation sets used for model...

The objective of this contribution is to form a clear picture of uncertainties we encounter in flood estimation, including both real-time flood forecasting and simulation for flood risk estimation. In simulation, we prefer the thesis of equifinality to obtain global optima. Many models producing...

It may be endemic to mechanistic modelling of complex environmental systems that there are many different model structures and many different parameter sets within a chosen model structure that may be behavioural or acceptable in reproducing the observed behaviour of that system. This has been...

Quantitative modeling of risk and hazard from flooding involves decisions regarding the choice of model and goal of the modeling exercise, expressed by some measure of performance. This paper shows how the subjectivity in the choices of performance measures and observation sets used for model...

This article provides an extended response to the criticisms of the GLUE methodology by Mantovan and Todini [Mantovan, P., Todini, E., 2006. Hydrological forecasting uncertainty assessment: incoherence of the GLUE methodology. J. Hydrol. 330, 368–381]. It is shown that the formal Bayesian...

Operational flood forecasting requires accurate forecasts with a suitable lead time, in order to be able to issue appropriate warnings and take appropriate emergency actions. Recent improvements in both flood plain characterization and computational capabilities have made the use of distributed...

Parameter estimation in nonlinear models is a common task, and one for which there is no general solution at present. In the case of linear models, the distribution of forecast errors provides a reliable guide to parameter estimation, but in nonlinear models the facts that predictability may...

This work is motivated by dose-finding studies, where the number of events per subject within a specified study period form the primary outcome. The aim of the considered studies is to identify the target dose for which the new drug can be shown to be as effective as a competitor medication....

Pharmacokinetic studies are commonly analyzed using a two-stage approach where the first stage involves estimation of pharmacokinetic parameters for each subject separately and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not...