Andrianov G., Burriel S., Cambier S., Dutfoy A., Dutka-Malen I., de Rocquigny E., Sudret B., Benjamin P., Lebrun R., Mangeant F., Pendola M. (2007) Open TURNS, an Open Source initiative to Treat Uncertainties Risks’N Statistics in a structured industrial approach, Proc. of ESREL 2007, Stavanger, Norway

Apostolakis G. (1990) The Concept of Probability in Safety Assessments of Technological Systems. *Science *1990;250(4986):1359-1364.

Apostolakis, G. (1999). The distinction between aleatory and epistemic uncertainties is important; an example from the inclusion of aging effects in the PSA. PSA'99, Washington DC, USA.

Aven, T. (2003), *Foundations of Risk Analysis*, Wiley

Beck, J.V. and Arnold, K.J. (1977) *Parameter Estimation in Engineering and Science*, Wiley.

Beck, M.B. (1987) Water Quality Modeling: A Review of the Analysis of Uncertainty, *Wat. Res. Research*, Vol. 23, No 8:1393-1442.

Bedford T., Cooke R. (2001), *Probabilistic Risk Analysis – Foundations and Methods*, Cambridge University Press

Cacuci, D.G., et al. (1980), *Sensitivity Theory for General Systems of Nonlinear Equations*, Nucl. Sc. & Eng. 75

Celeux G., Grimaud A., Lefebvre Y., de Rocquigny E. (2007), Identifying intrinsic variability in multi-variate systems through linearised inverse methods, *INRIA Research Report*, December 2007

Cooke R. (2001), *Experts in Uncertainty*, Oxford University Press, New York

Cover T.M. and Thomas J.A. (1990, 2006), *Elements of Information Theory*, Wiley

De Crécy, A. (1997) CIRCE: a tool for calculating the uncertainties of the constitutive relationships of Cathare2, *8*^{th}* International Topical Meeting on Nuclear reactor Thermo-Hydraulics (NURETH8)*, Kyoto.

de Rocquigny E. (2006) La maîtrise des incertitudes dans un contexte industriel: 1^{ère} partie – une approche méthodologique globale basée sur des exemples; 2^{nd} partie – revue des méthodes de modélisation statistique, physique et numérique.* Journal de la Société Française de Statistique*, vol. 147, n° 4, 33-106.

de Rocquigny E., Cambier S. (2008) Inverse probabilistic modeling through non-parametric simulated likelihood, Pre-print submitted to *Inverse Problems in Science and Engineering*.

de Rocquigny E., Devictor N., Tarantola S. (editors) (2008) *Uncertainty in industrial practice, A guide to quantitative uncertainty management*, Wiley.

Dempster, A. P. (1967). Upper and lower probabilities induced by a multi-valued mapping, Annals of Math. Statistics 38: 325-339.

Dupuy, J.P. (2002), *Pour un catastrophisme éclairé – Quand l’Impossible est certain*, Ed. du Seuil

Ellingwood BR. Probability-based codified design: past accomplishments and future challenges. Structural Safety 1994 ;13:159-176.

Frey, H.C., Rhodes D.S. (2005), *Quantitative Analysis of Variability and Uncertainty in with Known Measurement Error : Methodology and Case Study*, Risk Analysis Vol. 25, N°3

Granger Morgan, M., Henrion M. (1990) *Uncertainty – A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis*, Cambridge University Press.

Hamby DM. (1994) A Review of Techniques for Parameter Sensitivity Analysis of Environmental Models. *Environmental Monitoring and Assessment *1994;32(2):135-154.

Helton, J. (1993) Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal, *Rel. Eng. & Syst. Saf.*, 42, 327-367.

Helton, J.C., Burmaster, D.E. (1996) Guest Editorial : Treatment of Aleatory and Epistemic Uncertainty in Performance Assessments for Complex Systems, *Rel. Eng. & Syst. Saf.*, 1996;54(2-3):91-94.

Helton, J.C., Oberkampf W.L. (editors) (2004) Alternative Representations of Epistemic Uncertainty, Special Issue of *Rel. Eng. & Syst. Saf.*, vol. 85 n°1-3.

ISO GUM (1995), *Guide to the expression of uncertainty in measurement (G.U.M.), *European Pre-Standard ENV 13005

Knight, F.H. (1921), *Risk, Uncertainty and Profit*, Hart, Schaffner & Marx

Kurowicka, D., and Cooke, R.M. (2002), *Techniques for generic probabilistic inversion, Probabilistic Safety Assessment and Management*, E.J. Bonano et al. (eds), Elsevier, 1543-1550.

Madsen HO, Kenk S & Lind NC (1986). Methods of Structural Safety, Prentice-Hall Inc.

Oberkampf, W.L. et al. (2002), *Error and uncertainty in modeling and simulation*, Rel. Eng. & Sys. Saf., 75

Parry GW, Winter PW. (1981) Characterization and Evaluation of Uncertainty in Probabilistic Risk Analysis. *Nuclear Safety *1981;22(1):28-42.

Paté-Cornell ME. (1996) Uncertainties in Risk Analysis: Six Levels of Treatment *Reliability Engineering and System Safety *1996;54(2-3):95-111.

Quiggin J., (1982), *a theory of anticipated utility*, Journal of Economic Behavior and Organization, vol 3, pp 323-343

Rubinstein RY. (1981) *Simulation and the Monte-Carlo Method*. Wiley. and Rubinstein R.Y., Kroese D.P. (2007)* Simulation and the Monte-Carlo Method*, 2^{nd} edition, Wiley.

Saltelli A., Tarantola, S., Campolongo F. & Ratto M. (2004) *Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models*, John Wiley and Sons.

Savage L.H. (1957), *The Foundations of Statistics*, Dover Publication Inc.

Shannon, C.E., (1948), *A mathematical theory of communication*, Bell Systems Technical Journal 27

Sobol, I.M. (1993), *Sensitivity estimates for non-linear mathematical models*, Mathematical Modeling and Computational Experiments

Talagrand, O. (1997) Assimilation of observations, an introduction, *J. Meteor. Soc. Japan*, 75, 191-201.

Tarantola, A. (1987) *Inverse Problem Theory and methods for data fitting and model parameter estimation*, Elsevier - Amsterdam et Tarantola, A. (2004) *Inverse Problem Theory and methods for model parameter estimation*, SIAM.

Von Neumann J., Morgenstern O., (1944), *Theory of games and economic behavior*, Princeton University Press

Walter, E., Pronzato, L. (1994) *Identification de Modèles Paramétriques à partir de données expérimentales*, Coll. MASC, Masson.