Statistical inference with belief functions: A survey
Belief functions are a powerful and popular framework for the mathematical characterisation of uncertainty, in particular in situations in which lack of data renders learning a probability distribution for the problem impractical. The first step in a reasoning chain based on belief functions is inference: how to learn a belief measure from the available data. In this survey we focus, in particular, on making inference from statistical data, and review the most significant contributions in the area.
| Authors | Fabio Cuzzolin |
|---|---|
| Primary category | math.ST |
| Published | 8 May 2026 |
| Last updated at source | 8 May 2026 |
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