Abstract Discrete hazard models are widely applied for the analysis of time-to-event outcomes that intrinsically discrete or grouped versions continuous event times. Commonly, one assumes effect explanatory variables on can be described by a linear predictor function. This, however, may not appropriate when non-linear effects interactions between occur in data. To address this issue, we propose...

BACKGROUND Previous studies have suggested that epidemiological reasoning needs a fine-grained modelling of events, especially their spatial and temporal attributes. While the temporal analysis of events has been intensively studied, far less attention has been paid to their spatial analysis. This article aims at filling the gap concerning automatic event-spatial attribute analysis in order to ...

Consider the problem of predicting the occurrence of an event, the onset of diabetes mellitus, say, from a vector of continuous and discrete predictors. We propose a new algorithm for the construction of a tree-structured predictor for the event of interest, which uses a new approach for dealing with continuous predictors. The novelty is that the tree uses splits for continuous variables. This ...

We consider a stochastic financial exchange economy with a finite date-event tree representing time and uncertainty and a nominal financial structure with possibly long-term assets. We exhibit a sufficient condition under which the payoff matrix and the full payoff matrix have the same rank. This generalizes previous results of Angeloni-Cornet and MagillQuinzii involving only short-term assets....

When the failure probability of a system is extremely small or necessary statistical data from the system is scarce, it is very difficult or impossible to evaluate its reliability and safety with conventional fault tree analysis (FTA) techniques. New techniques are needed to predict and diagnose such a system’s failures and evaluate its reliability and safety. In this paper, we first provide a ...