C. Baudrit, I. Couso, and D. Dubois, Joint propagation of probability and possibility in risk analysis: Towards a formal framework, International Journal of Approximate Reasoning, vol.45, issue.1, pp.45-82, 2007.
DOI : 10.1016/j.ijar.2006.07.001

A. S. Bertoluzza, A. Salas, and N. Corral, On a new class of distances between fuzzy numbers, Mathw. Soft Comput, vol.2, pp.71-84, 1995.

A. Blanco-fernández, A distance-based statistical analysis of fuzzy number-valued data, International Journal of Approximate Reasoning, vol.55, issue.7, pp.1487-1501, 2014.
DOI : 10.1016/j.ijar.2013.09.020

R. Boukezzoula, S. Galichet, and A. Bisserier, A Midpoint???Radius approach to regression with interval data, International Journal of Approximate Reasoning, vol.52, issue.9, pp.1257-1271, 2011.
DOI : 10.1016/j.ijar.2011.07.002
URL : https://hal.archives-ouvertes.fr/hal-00633518

Y. Chalco-cano and H. Román-flores, Some remarks on fuzzy differential equations via differential inclusions, Fuzzy Sets Syst, 2013.

A. Colubi, Statistical inference about the means of fuzzy random variables: Applications to the analysis of fuzzy-and real-valued data, Fuzzy Sets and Systems, pp.344-356, 2009.

A. Colubi, G. González-rodríguez, M. A. Gil, and W. Trutschnig, Nonparametric criteria for supervised classification of fuzzy data, International Journal of Approximate Reasoning, vol.52, issue.9, pp.52-1272, 2011.
DOI : 10.1016/j.ijar.2011.05.007

O. Cordón, A historical review of evolutionary learning methods for Mamdani-type fuzzy rule-based systems: Designing interpretable genetic fuzzy systems, International Journal of Approximate Reasoning, vol.52, issue.6, pp.894-913, 2011.
DOI : 10.1016/j.ijar.2011.03.004

I. Couso and D. Dubois, On the Variability of the Concept of Variance for Fuzzy Random Variables, IEEE Transactions on Fuzzy Systems, vol.17, issue.5, pp.1070-1080, 2009.
DOI : 10.1109/TFUZZ.2009.2021617

I. Couso and S. , Independence concepts in evidence theory, International Journal of Approximate Reasoning, vol.51, issue.7, pp.748-758, 2010.
DOI : 10.1016/j.ijar.2010.02.004

I. Couso, S. Montes, and P. Gil, The necessity of the strong ?-cuts, Int. J. Uncertain. Fuzziness Knowledge-Based Systems, vol.9, issue.249, 2001.

I. Couso, S. Moral, and P. Walley, A survey of concepts of independence for imprecise probabilities, Risk Decision and Policy, vol.5, issue.2, pp.165-181, 2000.
DOI : 10.1017/S1357530900000156

I. Couso and L. Sánchez, Higher order models for fuzzy random variables, Fuzzy Sets and Systems, pp.237-258, 2008.

I. Couso and L. Sánchez, Upper and lower probabilities induced by a fuzzy random variable, Fuzzy Sets and Systems, pp.1-23, 2011.

I. Couso and L. Sánchez, Mark-recapture techniques in statistical tests for imprecise data, International Journal of Approximate Reasoning, vol.52, issue.2, pp.240-260, 2011.
DOI : 10.1016/j.ijar.2010.07.009

L. M. De-campos, M. T. Lamata, and S. , The concept of conditional fuzzy measure, International Journal of Intelligent Systems, vol.38, issue.3, pp.237-246, 1990.
DOI : 10.1002/int.4550050302

G. De-cooman and P. Walley, An imprecise hierarchical model for behaviour under uncertainty, Theory and Decision, vol.52, issue.4, pp.327-374, 2002.
DOI : 10.1023/A:1020296514974

A. P. Dempster, Upper and Lower Probabilities Induced by a Multivalued Mapping, The Annals of Mathematical Statistics, vol.38, issue.2, pp.325-339, 1967.
DOI : 10.1214/aoms/1177698950

T. Denoeux, Maximum likelihood estimation from fuzzy data using the EM algorithm, Fuzzy Sets and Systems, vol.183, issue.1, pp.72-91, 2011.
DOI : 10.1016/j.fss.2011.05.022
URL : https://hal.archives-ouvertes.fr/hal-00654118

T. Denoeux, Z. Younes, and F. Abdallah, Representing uncertainty on set-valued variables using belief functions, Artificial Intelligence, vol.174, issue.7-8, pp.7-8, 2010.
DOI : 10.1016/j.artint.2010.02.002
URL : https://hal.archives-ouvertes.fr/hal-00467932

P. Diamond, Fuzzy least squares, Information Sciences, vol.46, issue.3, pp.141-157, 1988.
DOI : 10.1016/0020-0255(88)90047-3

P. Diamond and P. Kloeden, Metric Spaces of Fuzzy Sets, World Scientific, 1994.

D. Dubois, Possibility theory and statistical reasoning, Computational Statistics & Data Analysis, vol.51, issue.1, pp.47-69, 2006.
DOI : 10.1016/j.csda.2006.04.015

D. Dubois, The role of fuzzy sets in decision sciences: Old techniques and new directions, Fuzzy Sets and Systems, pp.3-28, 2011.

D. Dubois and T. Denoeux, Conditioning in Dempster-Shafer Theory: Prediction vs. Revision, Belief Functions Advances in Soft Computing, pp.2012-385
DOI : 10.1007/978-3-642-29461-7_45

D. Dubois, L. Foulloy, G. Mauris, and H. Prade, Probability-Possibility Transformations, Triangular Fuzzy Sets, and Probabilistic Inequalities, Reliable Computing, vol.10, issue.4, pp.273-297, 2004.
DOI : 10.1023/B:REOM.0000032115.22510.b5

D. Dubois, H. Prade31, ]. D. Dubois, H. Prade, R. Fagin et al., Incomplete conjunctive information Prade, When upper probabilities are possibility measures The three semantics of fuzzy sets, Fuzzy Sets and Systems Prade, Gradualness, uncertainty and bipolarity: Making sense of fuzzy sets, Fuzzy Sets and Systems 192 (2012) 3?24 A new approach to updating beliefs, Uncertainty in Artificial Intelligence, UAI'91, pp.797-810, 1988.

M. B. Ferraro, R. Coppi, G. González-rodríguez, and A. Colubi, A linear regression model for imprecise response, International Journal of Approximate Reasoning, vol.51, issue.7, pp.51-759, 2010.
DOI : 10.1016/j.ijar.2010.04.003

S. Ferson, L. Ginzburg, V. Kreinovich, L. Longpre, and M. Aviles, Computing variance for interval data is NP-hard, ACM SIGACT News, vol.33, issue.2, pp.108-118, 2002.
DOI : 10.1145/564585.564604
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.16.7263

J. Gebhardt, M. A. Gil, and R. Kruse, Fuzzy set-theoretic methods in statistics Fuzzy Sets in Decision Analysis, Operations Research and Statistics, pp.311-347, 1998.

G. González-rodríguez, A. Blanco, A. Colubi, and M. A. Lubiano, Estimation of a simple linear regression model for fuzzy random variables, Fuzzy Sets and Systems, vol.160, issue.3, pp.357-370, 2009.
DOI : 10.1016/j.fss.2008.07.007

G. González-rodríguez, A. Colubi, and M. A. Gil, Fuzzy data treated as functional data: A one-way ANOVA test approach, Computational Statistics & Data Analysis, vol.56, issue.4, pp.943-955, 2012.
DOI : 10.1016/j.csda.2010.06.013

J. Y. Jaffray, Bayesian updating and belief functions, IEEE Transactions on Systems, Man, and Cybernetics, vol.22, issue.5, pp.1144-1152, 1992.
DOI : 10.1109/21.179852

R. Körner, On the variance of fuzzy random variables, Fuzzy Sets and Systems, pp.83-93, 1997.

A. Herzig, J. Lang, and P. Marquis, Action representation and partially observable planning using epistemic logic, Proc. Int. Joint Conf. on Artificial Intelligence, IJCAI-03, pp.1067-1072, 2003.

E. Huellermeier, An Approach to Modelling and Simulation of Uncertain Dynamical Systems, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol.05, issue.02, pp.117-137, 1997.
DOI : 10.1142/S0218488597000117

D. G. Kendall, Foundations of a theory of random sets, Stochastic Geometry, pp.322-376, 1974.

V. Kreinovich, G. Xiang, and S. Ferson, Computing mean and variance under Dempster???Shafer uncertainty: Towards faster algorithms, International Journal of Approximate Reasoning, vol.42, issue.3, pp.212-227, 2006.
DOI : 10.1016/j.ijar.2005.12.001
URL : http://doi.org/10.1016/j.ijar.2005.12.001

R. Kruse and K. Meyer, Statistics with Vague Data, D. Reidel, Dordrecht, The Netherlands, 1987.

H. Kwakernaak, Fuzzy random variables???I. definitions and theorems, Information Sciences, vol.15, issue.1, pp.1-29, 1978.
DOI : 10.1016/0020-0255(78)90019-1

H. Kwakernaak, Fuzzy random variables???II. Algorithms and examples for the discrete case, Information Sciences, vol.17, issue.3, pp.253-278, 1979.
DOI : 10.1016/0020-0255(79)90020-3

D. V. Lindley, Scoring Rules and the Inevitability of Probability, International Statistical Review / Revue Internationale de Statistique, vol.50, issue.1, pp.1-26, 1982.
DOI : 10.2307/1402448

K. Loquin and D. Dubois, Kriging and Epistemic Uncertainty: A Critical Discussion, Methods for Handling Imperfect Spatial Information, pp.269-305, 2010.
DOI : 10.1007/978-3-642-14755-5_11

K. Loquin and D. Dubois, Kriging with Ill-Known Variogram and Data, Scalable Uncertainty Management, SUM 2010, pp.219-235, 2010.
DOI : 10.1007/978-3-642-15951-0_23

G. Matheron, Random Sets and Integral Geometry, 1975.

R. Moore, Methods and Applications of Interval Analysis, Studies in Applied Mathematics, 1979.
DOI : 10.1137/1.9781611970906

H. T. Nguyen, On random sets and belief functions, Journal of Mathematical Analysis and Applications, vol.65, issue.3, pp.531-542, 1978.
DOI : 10.1016/0022-247X(78)90161-0

J. Paris, The Uncertain Reasoner's Companion, 1994.

F. Pichon, D. Dubois, and T. Denoeux, Relevance and truthfulness in information correction and fusion, International Journal of Approximate Reasoning, vol.53, issue.2, pp.159-175, 2012.
DOI : 10.1016/j.ijar.2011.02.006
URL : https://hal.archives-ouvertes.fr/hal-00656775

H. Prade and M. Serrurier, Maximum-likelihood principle for possibility distributions viewed as families of probabilities, IEEE International Conference on Fuzzy Systems, pp.2987-2993, 2011.

M. Puri and D. Ralescu, Fuzzy random variables, Journal of Mathematical Analysis and Applications, vol.114, issue.2, pp.409-422, 1986.
DOI : 10.1016/0022-247X(86)90093-4

A. B. Ramos-guajardo and M. A. Lubiano, -sample tests for equality of variances of random fuzzy sets, Computational Statistics & Data Analysis, vol.56, issue.4, pp.956-966, 2012.
DOI : 10.1016/j.csda.2010.11.025

G. L. Shackle, Decision, Order and Time in Human Affairs, 1961.

G. Shafer, A Mathematical Theory of Evidence, 1976.

G. Shafer and A. Tversky, Languages and Designs for Probability Judgment*, Cognitive Science, vol.238, issue.3, pp.309-339, 1985.
DOI : 10.1207/s15516709cog0903_2

M. Spadoni and L. Stefanini, Computing the variance of interval and fuzzy data, Fuzzy Sets and Systems, pp.24-36, 2011.

L. Sánchez, I. Couso, and J. Casillas, Genetic learning of fuzzy rules based on low quality data, Fuzzy Sets and Systems, pp.2524-2552, 2009.

L. Sánchez and I. Couso, Advocating the Use of Imprecisely Observed Data in Genetic Fuzzy Systems, IEEE Transactions on Fuzzy Systems, vol.15, issue.4, pp.551-562, 2007.
DOI : 10.1109/TFUZZ.2007.895942

L. Sánchez and I. Couso, Learning from imprecise examples with GA-P algorithms, Mathw. Soft Comput, vol.23, issue.5, pp.305-319, 1998.

L. Sánchez, J. Otero, and I. Couso, Obtaining linguistic fuzzy rule-based regression models from imprecise data with multiobjective genetic algorithms, Soft Comput, pp.307-318, 2009.

P. Smets, The normative representation of quantified beliefs by belief functions, Artificial Intelligence, vol.92, issue.1-2, pp.229-242, 1997.
DOI : 10.1016/S0004-3702(96)00054-9

H. Tanaka and P. Guo, Possibilistic Data Analysis for Operations Research, 1999.

W. Trutschnig, G. González-rodríguez, A. Colubi, and M. A. Gil, A new family of metrics for compact, convex (fuzzy) sets based on a generalized concept of mid and spread???, Information Sciences, vol.179, issue.23, pp.179-3964, 2009.
DOI : 10.1016/j.ins.2009.06.023

W. Trutschnig, M. A. Lubiano, and J. Lastra, SAFD ? An R package for statistical analysis of fuzzy data in towards advanced data analysis by combining soft computing and statistics, Studies in Fuzziness and Soft Computing, pp.107-118, 2013.

P. Walley, Statistical Reasoning with Imprecise Probabilities, 1991.
DOI : 10.1007/978-1-4899-3472-7

R. R. Yager, Set-based representations of conjunctive and disjunctive knowledge, Information Sciences, vol.41, issue.1, pp.1-22, 1987.
DOI : 10.1016/0020-0255(87)90002-8

J. Yen, Generalizing the Dempster???Shafer Theory to Fuzzy Sets, IEEE Trans. Syst. Man Cybern, vol.20, pp.559-569, 1990.
DOI : 10.1007/978-3-540-44792-4_21

L. A. Zadeh, The concept of a linguistic variable and its application to approximate reasoning???I, Information Sciences, vol.8, issue.3, pp.199-249, 1975.
DOI : 10.1016/0020-0255(75)90036-5

L. A. Zadeh, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, vol.1, pp.1-28, 1978.

L. A. Zadeh, PRUF???a meaning representation language for natural languages, International Journal of Man-Machine Studies, vol.10, issue.4, pp.395-460, 1978.
DOI : 10.1016/S0020-7373(78)80003-0