Skip to main content

Set-Valued Stochastic Processes and Sets of Probability Measures Induced by Stochastic Differential Equations with Random Set Parameters

  • Conference paper
Combining Soft Computing and Statistical Methods in Data Analysis

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 77))

  • 1612 Accesses

Abstract

We consider stochastic differential equations depending on parameters whose uncertainty is modeled by random compact sets. Several approaches are discussed how to construct set-valued processes from the solutions. The induced lower and upper probabilities are compared to a set of probability measures constructed from the distributions of the solutions and the selections of the random set.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Billingsley, P.: Probability and measure. Wiley, New York (1986)

    MATH  Google Scholar 

  2. Castaing, C., Valadier, M.: Convex analysis and measurable multifunctions. Springer, Berlin (1977)

    MATH  Google Scholar 

  3. Castaldo, A., Marinacci, M.: Random correspondences as bundles of random variables. In: De Cooman, G., Fine, T., Seidenfeld, T. (eds.) Proceedings of the Second International Symposium on Imprecise Probabilities and Their Applications, ISIPTA 2001, Ithaca, NY, USA, pp. 77–82. Shaker Publishing, Maastricht (2001)

    Google Scholar 

  4. Choquet, G.: Theory of capacities. Ann. Inst. Fourier, Grenoble 5(1953-1954), 131–295 (1955)

    MathSciNet  Google Scholar 

  5. Dempster, A.P.: Upper and lower probabilities induced by a multivalued mapping. Ann. Math. Statist. 38, 325–339 (1967)

    Article  MATH  MathSciNet  Google Scholar 

  6. Denneberg, D.: Non-additive measure and integral. Kluwer, Dordrecht (1994)

    MATH  Google Scholar 

  7. Fetz, T., Oberguggenberger, M.: Propagation of uncertainty through multivariate functions in the framework of sets of probability measures. Reliab. Eng. Syst. Saf. 85, 73–88 (2004)

    Article  Google Scholar 

  8. Fetz, T.: Multiparameter models: Probability distributions parameterized by random sets. In: De Cooman, G., Vejnarova, J., Zaffalon, M. (eds.) Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications, ISIPTA 2007, Prague, Czech Republic, pp. 183–192. Action M Agency for SIPTA (2007)

    Google Scholar 

  9. Gikhman, I.I., Skorokhod, A.V.: Stochastic differential equations. Springer, New York (1972)

    MATH  Google Scholar 

  10. Hiai, F., Umegaki, H.: Integrals, conditional expectations, and martingales of multivalued functions. J. Multivariate Anal. 7, 149–182 (1977)

    Article  MATH  MathSciNet  Google Scholar 

  11. Himmelberg, C.J.: Measurable relations. Fund. Math. 87, 53–72 (1975)

    MATH  MathSciNet  Google Scholar 

  12. Li, S., Ren, A.: Representation theorems, set-valued and fuzzy set-valued Itô integral. Fuzzy Sets Syst. 158, 949–962 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  13. Li, J., Li, S.: Set-Valued Stochastic Lebesgue Integral and Representation Theorems. Int. J. Comput. Intell. Syst. 1, 177–187 (2008)

    Google Scholar 

  14. Li, J., Li, S.: Itô Type Set-Valued Stochastic Differential Equation. J. Uncertain Syst. 3, 52–63 (2009)

    Google Scholar 

  15. Miranda, E., Couso, I., Gil, P.: Random sets as imprecise random variables, J. Math. Anal. Appl. 307, 32–47 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  16. Miranda, E., Couso, I., Gil, P.: Approximations of upper and lower probabilities by measurable selections. Inform. Sci. 180, 1407–1417 (2010)

    Article  MATH  Google Scholar 

  17. Molchanov, I.: Theory of random sets. Springer, London (2005)

    MATH  Google Scholar 

  18. Schmelzer, B.: On solutions of stochastic differential equations with parameters modelled by random sets. Internat. J. Approx. Reason. (accepted for publication, 2010)

    Google Scholar 

  19. Schmelzer, B., Oberguggenberger, M., Adam, C.: Efficiency of Tuned Mass Dampers with Uncertain Parameters on the Performance of Structures under Stochastic Excitation. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability (accepted for publication, 2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Schmelzer, B. (2010). Set-Valued Stochastic Processes and Sets of Probability Measures Induced by Stochastic Differential Equations with Random Set Parameters. In: Borgelt, C., et al. Combining Soft Computing and Statistical Methods in Data Analysis. Advances in Intelligent and Soft Computing, vol 77. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14746-3_69

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-14746-3_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14745-6

  • Online ISBN: 978-3-642-14746-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics