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...

Public support for private R&D and innovation is part of most national and regional innovation support regimes. In this article, we estimate the effect of public innovation support oil innovation outputs in Ireland and Northern Ireland. Three dimensions of output additionality are, considered...

Love J. H., Roper S. and Hewitt-Dundas N. Service innovation, embeddedness and business performance: evidence from Northern Ireland, Regional Studies. This paper explores the factors that determine innovation by service firms, and in particular the contribution of intra- and extra-regional...

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,...

The paper compares non-parametric (design-based) and parametric (model-based) approaches to the analysis of data in the form of replicated spatial point patterns in two or more experimental groups. Basic questions for data of this kind concern estimating the properties of the underlying spatial...

Stone's isotonic regression method for analysing count data to estimate disease risk in relation to a point source of environmental pollution is now routinely used. This paper develops the corresponding procedure for case-control data consisting of the locations of individual cases with controls...