Arithmetic and other operations on Dempster-Shafer structures
International Journal of Man-Machine Studies
Probabilistic arithmetic. I. numerical methods for calculating convolutions and dependency bounds
International Journal of Approximate Reasoning
Random sets and fuzzy interval analysis
Fuzzy Sets and Systems - Special issue on mathematical aspects of fuzzy sets
Joint propagation of probability and possibility in risk analysis: Towards a formal framework
International Journal of Approximate Reasoning
A survey of the theory of coherent lower previsions
International Journal of Approximate Reasoning
Representing parametric probabilistic models tainted with imprecision
Fuzzy Sets and Systems
Bayesian learning for a class of priors with prescribed marginals
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
Unifying practical uncertainty representations -- I: Generalized p-boxes
International Journal of Approximate Reasoning
Computing expectations with continuous p-boxes: Univariate case
International Journal of Approximate Reasoning
Practical representations of incomplete probabilistic knowledge
Computational Statistics & Data Analysis
Probability boxes on totally preordered spaces for multivariate modelling
International Journal of Approximate Reasoning
Eliciting density ratio classes
International Journal of Approximate Reasoning
On the connection between probability boxes and possibility measures
Information Sciences: an International Journal
On an implicit assessment of fuzzy volatility in the Black and Scholes environment
Fuzzy Sets and Systems
International Journal of Approximate Reasoning
Stochastic dominance with imprecise information
Computational Statistics & Data Analysis
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We apply belief functions to an analysis of future climate change. It is shown that the lower envelope of a set of probabilities bounded by cumulative probability distributions is a belief function. The large uncertainty about natural and socio-economic factors influencing estimates of future climate change is quantified in terms of bounds on cumulative probability. This information is used to construct a belief function for a simple climate change model, which then is projected onto an estimate of global mean warming in the 21st century. Results show that warming estimates on this basis can generate very imprecise uncertainty models.