Forecasting using belief functions: An application to marketing econometrics
A method is proposed to quantify forecast uncertainty using belief functions. The method is simple and can be applied to any parametric statistical model. The approach does not require to specify a prior distribution on the parameter. The Bayesian approach is recovered as a special case when a prior is provided. The method is applied to innovation diffusion forecasting using the Bass model.
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