Uncertain Reasoning and Forecasting », International Journal of Forecasting, 1995, p. 73-87., , et , «
A probability forecasting model is developed through a synthesis of Bayesian belief-network models and classical time-series analysis. Using richer models it is possible to go beyond the rigid assumptions of linearity in the relationships among variables. The methodology is applied to the difficult problem of predicting outcome in critically ill patients. This highlighted the need for a synthesis of probability forecasting and uncertain reasoning.
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