We propose a stochastic model for the analysis of time series of disease counts as collected in typical surveillance systems on notifiable infectious diseases. The model is based on a Poisson or negative binomial observation model with two components: A parameter-driven component relates the...

In this paper we consider regression models for count data allowing for overdispersion in a Bayesian framework. Besides the inclusion of covariates, spatial effects are incorporated and modelled using a proper Gaussian conditional autoregressive prior based on Pettitt et al. (2002). Apart from...

Diese Arbeit ist die erste empirische Untersuchung, die den Wert eines statistischen Lebens (WSL) für die Bundesrepublik Deutschland ermittelt. Die Analysen werden auf der Grundlage eines aus IAB-Beschäftigtenstichprobe und Arbeitsunfallinformationen der Berufsgenossenschaften...

Overdispersion in count data regression is often caused by neglection or inappropriate modelling of individual heterogeneity, temporal or spatial correlation, and nonlinear covariate effects. In this paper, we develop and study semiparametric count data models which can deal with these issues by...