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Enrique Miranda



Enrique Miranda is a full professor at the Department of Statistics and Operations Research at the University of Oviedo (Spain). Between 2003 and 2008 he was assistant professor at Rey Juan Carlos University in Madrid (Spain). His research has focused on different aspects of imprecise probability theory. Imprecise probabilities arise in situations where the existence of imprecise or vague information makes it unadvaisable to work with a precise and unique probability distribution. In those situations, it may be useful (and more reasonable) to consider alternative models, such as sets of probability measures, upper and lower probabilities, Choquet capacities, etc. In his work, he has studied some of the theoretical challenges that arise with these models, and more specifically investigated coherent lower previsions, sets of desirable gambles, random sets, and non-additive measures. In addition, he has served at the Executive Committee of the Society for Imprecise Probabilities: Theories and Publications (SIPTA), of which he is currently President, and he is at the editorial board of the International Journal of Approximate Reasoning. You can find more detailed information at www.mirandaenrique.com.

Selected publications:

  1. Enrique Miranda, Inés Couso and Pedro Gil. Random intervals as a model for imprecise information. Fuzzy Sets and Systems, 154(3), 386-412, 2005.
  2. Gert de Cooman and Enrique Miranda. Weak and strong laws of large numbers for cohwerent lower previsions. Journal of Statistical Planning and Inference, 138(8), 2008.
  3. Ignacio Montes, Enrique Miranda, Susana Montes. Decision making with imprecise utilities and belief by means of statistical preference and stochastic dominance. European Journal of Operational Research, 231(1), 209-220, 2014. 
  4. Enrique Miranda and Sébastien Destercke. Extreme points of the credal sets generated by comparative probabilities. Journal of Mathematical Psychology, 64/65, 44-57, 2015.
  5. Ariana Casanova, Enrique Miranda, Marco Zaffalon. Joint desirability foundations of social choice and opinion pooling. Annals of Mathematics and Artificial Intelligence, 89(10-11), 965-1011, 2021.

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