Skip to main content
Log in

Three digit accurate multiple normal probabilities

  • Published:
Numerische Mathematik Aims and scope Submit manuscript

Summary

Computer algorithms are presented for evaluating the multidimensional normal distribution function by Monte Carlo techniques. The computation of such probabilities is frequently required in stochastic programming models and in multivariate statistical problems. Using a medium size computer, three significant digits can be obtained up to ten dimensions in five seconds, up to twenty dimensions in one minute and up to fifty dimensions in ten minutes. Results of the detailed computer experiences are also reported together with some numerical examples.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Ahrens, J.H., Dieter, U.: Computer methods for sampling from gamma, beta, Poisson and binomial distributions, Computing12, 223–246 (1974)

    Google Scholar 

  2. Davis, P.J., Rabinowitz, P.: Methods of numerical integration. New York: Academic Press (1975)

    Google Scholar 

  3. Deák, I.: Computing the probabilities of sets in higher dimensional spaces in case of normal distribution. Alkalmaz. Mat. Lapok2, 17–26 (1976) (in Hungarian)

    Google Scholar 

  4. Deák, I.: Monte Carlo methods for computing probabilities of sets in higher dimensional spaces in case of normal distribution. Alkalmaz. Mat. Lapok4, 35–94 (1978) (in Hungarian)

    Google Scholar 

  5. Deák, I.: Fast procedures for generating stationary normal vectors, J. Statist. Comp. and Simulation10, 225–242 (1980)

    Google Scholar 

  6. Deák, I.: Computation of multiple normal probabilities. Symposium on Stochastic Programming. Lecture Notes in Mathematics. (P. Kall, ed.) Berlin Heidelberg New York: Springer (in press, 1980)

    Google Scholar 

  7. Donelly, T.G.: Bivariate normal distribution. Comm. ACM16, 638 (1973)

    Google Scholar 

  8. Dutt, J.E.: A representation of multivariate normal probability integrals by integral transforms. Biometrika60, 637–645 (1973)

    Google Scholar 

  9. Gupta, S.S.: Probability integrals of multivariate normal and multivariate. Ann. Math. Stat.34, 792–828 (1963).

    Google Scholar 

  10. Hill, I.D., Pike, M.C.: Chi-squared integral. Comm. ACM10, 243–244 (1967)

    Google Scholar 

  11. Johnson, N.L., Kotz, S.: Distributions in statistics. IV. Vol. New York: John Wiley 1972

    Google Scholar 

  12. Knuth, D.E.: The art of computer programming. II. Vol. Reading Mass.: Addison Wesley 1969

    Google Scholar 

  13. Milton, R.C.: Computer evaluation of the multivariate normal integral. Technometrics14, 881–889 (1972)

    Google Scholar 

  14. Prékopa, A.: Contributions to the theory of stochastic programming. Math. Programming4, 202–221 (1973)

    Google Scholar 

  15. Prékopa, A., Ganczer, S., Deák, I., Patyi, K.: The STABIL stochastic programming model and its experimental application to the electrical energy sector of the Hungarian economy. In: Proceedings of the Internat. Symposium on Stochastic Programming (M. Dempster, ed.) Oxford: Academic Press. 1974

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Deák, I. Three digit accurate multiple normal probabilities. Numer. Math. 35, 369–380 (1980). https://doi.org/10.1007/BF01399006

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01399006

Subject Classifications

Navigation