Inferring probability densities from expert opinion
When experts are asked to assess a situation, they often express their opinions providing estimates of the probability of observing the occurrence of a random variable in given intervals, sometimes up to a range of values, rather than simply providing point estimates. The problem we face is how to t...
- Autores:
-
Gzyl, Henryk
ter Horst, Enrique
Molina, Germán
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2017
- Institución:
- Colegio de Estudios Superiores de Administración
- Repositorio:
- Repositorio CESA
- Idioma:
- eng
- OAI Identifier:
- oai:repository.cesa.edu.co:10726/5102
- Palabra clave:
- Maximum entropy method
Maximum entropy with errors in the data
Probability elicitation with uncertainty
- Rights
- openAccess
- License
- Abierto (Texto Completo)
| Summary: | When experts are asked to assess a situation, they often express their opinions providing estimates of the probability of observing the occurrence of a random variable in given intervals, sometimes up to a range of values, rather than simply providing point estimates. The problem we face is how to translate that expert opinion into probability distributions. We examine a novel way of solving that problem by making use of the maximum entropy method in the data to deal with expert opinions expressed with or without uncertainty bands. Our method allows us to unveil underlying probability distributions driving expert opinions expressed with and without uncertainty. |
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