[Binder, K. and Heermann, D. (1997). Monte Carlo Simulation in Statistical Physics, Springer Verlag, Berlin/Heidelberg.10.1007/978-3-662-03336-4]Search in Google Scholar
[Bjorck, A. (1996). Numerical Methods for Least Squares Problems, SIAM, Philadelphia, PA.10.1137/1.9781611971484]Search in Google Scholar
[Brandt, S. (1999). Data Analysis Statistical and Computational Methods for Scientists and Engineers, Springer-Verlag, New York, NY.]Search in Google Scholar
[Burczyński, T. (1995). Boundary element method in stochastic shape design sensitivity analysis and identification of uncertain elastic solids, Engineering Analysis with Boundary Elements15(2): 151–160.10.1016/0955-7997(95)00013-E]Search in Google Scholar
[Chakraverty, S. (2014). Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems, IGI Global, Hershey.10.4018/978-1-4666-4991-0]Search in Google Scholar
[Falsone, G. (2005). An extension of the Kazakov relationship for non-Gaussian random variables and its use in the non-linear stochastic dynamics, Probabilistic Engineering Mechanics20(1): 45–56.10.1016/j.probengmech.2004.06.001]Search in Google Scholar
[Feller, W. (1965). An Introduction to Probability Theory and Its Applications, Wiley, New York, NY.]Search in Google Scholar
[Grigoriu, M. (2000). Stochastic mechanics, International Journal of Solids and Structures37(1–2): 228–248.10.1016/S0020-7683(99)00088-8]Search in Google Scholar
[Hurtado, J. and Barbat, A. (1998). Monte-Carlo techniques in computational stochastic mechanics, Archives of Computer Methods in Engineering37(1): 3–30.10.1007/BF02736747]Search in Google Scholar
[Kamiński, M. (2005). Computational Mechanics of Composite Material, Springer-Verlag, London/New York, NY.]Search in Google Scholar
[Kamiński, M. (2013). The Stochastic Perturbation Method for Computational Mechanics, Wiley, Chichester.10.1002/9781118481844]Search in Google Scholar
[Kleiber, M. and Hien, T. (1992). The Stochastic Finite Element Method, Wiley, Chichester.]Search in Google Scholar
[Kwiatkowska, M., Norman, G., Sproston, J. and Wang, F. (2007). Symbolic model checking for probabilistic timed automata, Information and Computation205(7): 1027–1077.10.1016/j.ic.2007.01.004]Search in Google Scholar
[Kwiatkowska, M., Parker, D., Zhang, Y. and Mehmood, R. (2004). Dual-processor parallelisation of symbolic probabilistic model checking, 12th International Symposium Modeling, Analysis and simulation of Computer and Telecommunication Systems MASCOTS’04, Volendaam, The Netherlands, pp. 123–130.]Search in Google Scholar
[López, N., Nunez, M. and Rodriguez, I. (2006). Specification, testing and implementation relations for symbolic-probabilistic system, Theoretical Computer Science353(1–3): 228–248.10.1016/j.tcs.2005.10.047]Search in Google Scholar
[Melchers, R. (2002). Structural Reliability Analysis and Prediction, Wiley, Chichester.]Search in Google Scholar
[Moller, B. and Beer, M. (2004). Fuzzy Randomness. Uncertainty in Civil Engineering and Computational Mechanics, Springer-Verlag, Berlin/Heidelberg.10.1007/978-3-662-07358-2]Search in Google Scholar
[Nayfeh, A.H. (2000). Perturbation Method, Wiley-VCH Verlag GmbH, Weinheim.]Search in Google Scholar
[Peng, X., Geng, L., Liyan, W., Liu, G. and Lam, K. (1998). A stochastic finite element method for fatigue reliability analysis of gear teeth subjected to bending, Computational Mechanics21(3): 253–261.10.1007/s004660050300]Search in Google Scholar
[Sakata, S., Ashida, F., Kojima, T. and Zako, M. (2008). Three-dimensional stochastic analysis using a perturbation-based homogenization method for elastic properties of composite material considering microscopic uncertainty, International Journal of Solids and Structures45(3–4): 894–907.10.1016/j.ijsolstr.2007.09.008]Search in Google Scholar
[Schueller, G. (2007). On the treatment of uncertainties in structural mechanics and analysis, Computers and Structures85(5–6): 235–243.10.1016/j.compstruc.2006.10.009]Search in Google Scholar
[Shachter, R.D., D’Ambrosio, B. and Del Favero, B. (1990). Symbolic probabilistic inference in belief networks, Proceedings of the 8th National Conference on Artificial Intelligence AAAI-90, Boston, MA, USA, pp. 126–131.]Search in Google Scholar
[Shannon, C. (1948). A mathematical theory of communication, The Bell System Technical Journal27(4): 623–656.10.1002/j.1538-7305.1948.tb00917.x]Search in Google Scholar
[Sobczyk, K. and Spencer, B. (1992). Random Fatigue: From Data to Theory, Academic Press, Boston, MA.10.1016/B978-0-12-654225-7.50004-7]Search in Google Scholar
[Spanos, P. and Ghanem, R. (1991). Stochastic Finite Elements. A Spectral Approach, Springer-Verlag, Berlin/Heidelberg.]Search in Google Scholar
[To, C. and Kiu, M. (1994). Random responses of discretized beams and plates by the stochastic central difference method with time co-ordinate transformation, Computers and Structures53(3): 727–738.10.1016/0045-7949(94)90114-7]Search in Google Scholar
[Van Noortwijk, J. and Frangopol, D. (2004). Two probabilistic life-cycle maintenance models for deteriorating civil infrastructures, Probabilistic Engineering Mechanics19(4): 345–359.10.1016/j.probengmech.2004.03.002]Search in Google Scholar
[Wiggins, J. (1987). Option values under stochastic volatility. Theory and empirical evidence, Journal of Financial Economics19(2): 351–372.]Search in Google Scholar
[Zienkiewicz, O. and Taylor, R. (2005). Finite Element Method for Solid and Structural Mechanics, Elsevier, Amsterdam.]Search in Google Scholar