Imprecise stochastic orders and fuzzy rankings

We extend the notion of stochastic order to the pairwise comparison of fuzzy random variables. We consider expected utility, stochastic dominance and statistical preference, which are related to the comparisons of the expectations, distribution functions and medians of the underlying variables, and discuss how to generalize these notions to the fuzzy case, when an epistemic interpretation is given to the fuzzy random variables. In passing, we investigate to which extent the earlier extensions of stochastic dominance and expected utility to the comparison of sets of random variables can be useful as fuzzy rankings.

[1]  Jian-Bo Yang,et al.  Group decision making with expertons and uncertain generalized probabilistic weighted aggregation operators , 2014, Eur. J. Oper. Res..

[2]  A. Müller,et al.  Comparison Methods for Stochastic Models and Risks , 2002 .

[3]  Inés Couso,et al.  Upper and lower probabilities induced by a fuzzy random variable , 2011, Fuzzy Sets Syst..

[4]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[5]  J. Bezdek,et al.  A fuzzy relation space for group decision theory , 1978 .

[6]  Hepu Deng,et al.  Comparing and ranking fuzzy numbers using ideal solutions , 2014 .

[7]  Ana Colubi,et al.  Simulation of fuzzy random variables , 2009, Inf. Sci..

[8]  I. Gilboa,et al.  Maxmin Expected Utility with Non-Unique Prior , 1989 .

[9]  Inés Couso,et al.  Higher order models for fuzzy random variables , 2008, Fuzzy Sets Syst..

[10]  Didier Dubois,et al.  Possibility and Gradual Number Approaches to Ranking Methods for Random Fuzzy Intervals , 2012, IPMU.

[11]  J. Adamo Fuzzy decision trees , 1980 .

[12]  Ilya Molchanov,et al.  A stochastic order for random vectors and random sets based on the Aumann expectation , 2003 .

[13]  Didier Dubois,et al.  Random Sets and Random Fuzzy Sets as Ill-Perceived Random Variables: An Introduction for Ph.D. Students and Practitioners , 2014 .

[14]  Igor N. Rozenberg,et al.  Ranking probability measures by inclusion indices in the case of unknown utility function , 2014, Fuzzy Optim. Decis. Mak..

[15]  Susana Montes,et al.  Decision making with imprecise probabilities and utilities by means of statistical preference and stochastic dominance , 2014, Eur. J. Oper. Res..

[16]  M. Puri,et al.  Fuzzy Random Variables , 1986 .

[17]  Susana Montes,et al.  Stochastic Orders for Fuzzy Random Variables , 2014, SMPS.

[18]  Doheon Lee,et al.  Ranking the sequences of fuzzy values , 2004, Inf. Sci..

[19]  G. Choquet Theory of capacities , 1954 .

[20]  Etienne E. Kerre,et al.  Reasonable properties for the ordering of fuzzy quantities (II) , 2001, Fuzzy Sets Syst..

[21]  Radko Mesiar,et al.  Fuzzy Interval Analysis , 2000 .

[22]  Shan-Huo Chen Ranking fuzzy numbers with maximizing set and minimizing set , 1985 .

[23]  Inés Couso,et al.  Random intervals as a model for imprecise information , 2005, Fuzzy Sets Syst..

[24]  K. Kim,et al.  Ranking fuzzy numbers with index of optimism , 1990 .

[25]  Inés Couso,et al.  Approximations of upper and lower probabilities by measurable selections , 2010, Inf. Sci..

[26]  Ines Cousa Blanco Teoría de la probabilidad para datos imprecisos, algunos aspectos , 1999 .

[27]  G. Bortolan,et al.  A review of some methods for ranking fuzzy subsets , 1985 .

[28]  Susana Montes,et al.  Ranking fuzzy sets and fuzzy random variables by means of stochastic orders , 2015, IFSA-EUSFLAT.

[29]  Didier Dubois,et al.  An Imprecise Probability Approach to Joint Extensions of Stochastic and Interval Orderings , 2012, IPMU.

[30]  Marc Roubens,et al.  Ranking and defuzzification methods based on area compensation , 1996, Fuzzy Sets Syst..

[31]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[32]  D. Denneberg Non-additive measure and integral , 1994 .

[33]  Isaac Levi,et al.  The Enterprise Of Knowledge , 1980 .

[34]  L. Zadeh Fuzzy sets as a basis for a theory of possibility , 1999 .

[35]  J. K. Satia,et al.  Markovian Decision Processes with Uncertain Transition Probabilities , 1973, Oper. Res..

[36]  Dug Hun Hong,et al.  Multicriteria fuzzy decision-making problems based on vague set theory , 2000, Fuzzy Sets Syst..

[37]  Thierry Denux Extending stochastic ordering to belief functions on the real line , 2009 .

[38]  Didier Dubois,et al.  Kriging and Epistemic Uncertainty: A Critical Discussion , 2010, Methods for Handling Imperfect Spatial Information.

[39]  D. Dubois,et al.  The mean value of a fuzzy number , 1987 .

[40]  Peter Walley,et al.  STATISTICAL INFERENCES BASED ON A SECOND-ORDER POSSIBILITY DISTRIBUTION , 1997 .

[41]  Massimo Marinacci,et al.  Random Correspondences as Bundles of Random Variables , 2001 .

[42]  Matthias C. M. Troffaes Decision making under uncertainty using imprecise probabilities , 2007, Int. J. Approx. Reason..

[43]  Inés Couso,et al.  Second order possibility measure induced by a fuzzy random variable , 2002 .

[44]  Gert de Cooman,et al.  n-MONOTONE EXACT FUNCTIONALS , 2008 .

[45]  L. M. D. C. Ibáñez,et al.  A subjective approach for ranking fuzzy numbers , 1989 .

[46]  Chee Peng Lim,et al.  A new method for ranking fuzzy numbers and its application to group decision making , 2014 .

[47]  Mark A. McComb Comparison Methods for Stochastic Models and Risks , 2003, Technometrics.

[48]  Saeid Abbasbandy,et al.  Ranking of fuzzy numbers by sign distance , 2006, Inf. Sci..

[49]  Ching-Hsue Cheng,et al.  A new approach for ranking fuzzy numbers by distance method , 1998, Fuzzy Sets Syst..

[50]  P. Walley Statistical Reasoning with Imprecise Probabilities , 1990 .

[51]  R. Kruse,et al.  Statistics with vague data , 1987 .

[52]  Sébastien Destercke,et al.  Ranking of fuzzy intervals seen through the imprecise probabilistic lens , 2015, Fuzzy Sets Syst..

[53]  Didier Dubois,et al.  Ranking fuzzy numbers in the setting of possibility theory , 1983, Inf. Sci..

[54]  Susana Montes,et al.  Stochastic dominance with imprecise information , 2014, Comput. Stat. Data Anal..

[55]  Marco Zaffalon,et al.  Reliable diagnoses of dementia by the naive credal classifier inferred from incomplete cognitive data , 2003, Artif. Intell. Medicine.

[56]  Yufei Yuan Criteria for evaluating fuzzy ranking methods , 1991 .

[57]  Przemysław Grzegorzewski Statistical inference about the median from vague data , 1998 .

[58]  Moshe Shaked,et al.  Stochastic orders and their applications , 1994 .

[59]  Didier Dubois,et al.  An Extension of Stochastic Dominance to Fuzzy Random Variables , 2010, IPMU.

[60]  Enrique Miranda,et al.  A survey of the theory of coherent lower previsions , 2008, Int. J. Approx. Reason..

[61]  Bernard De Baets,et al.  A Fuzzy Approach to Stochastic Dominance of Random Variables , 2003, IFSA.