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...

A levy on the Clean Development Mechanism and other carbon trading schemes is a potential source of finance for climate change adaptation. An adaptation levy of 2% is currently imposed on all CDM transactions which could raise around $500 million between now and 2012. This paper analyses the...

Putting a price on carbon is critical for climate change policy. Increasingly, policymakers combine multiple policy tools to achieve this, for example by complementing cap-and-trade schemes with a carbon tax, or with a feed-in tariff. Often, the motivation for doing so is to limit undesirable...

The economic impact of climate change is usually measured as the extent to which the climate of a given period affects social welfare in that period. This static approach ignores the dynamic effects through which climate change may affect economic growth and hence future welfare. In this paper...

This paper discusses some of the elements that may characterise an efficient strategy to adapt to a changing climate. Such a strategy will have to reflect the long time horizon of, and the prevailing uncertainties about, climate change. An intuitively appealing approach therefore seems to be to...

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...

We consider the problem of semi-parametric regression modelling when the data consist of a collection of short time series for which measurements within series are correlated. The objective is to estimate a regression function of the form E[Y(t) | x] =x'ß+μ(t), where μ(.) is an arbitrary,...

Marginal models for multivariate binary data permit separate modelling of the relationship of the response with explanatory variables, and the association between pairs of responses. When the former is the scientific focus, a first-order generalized estimating equation method (Liang & Zeger,...