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Comparison of independent and stratified sampling schemes in problems of global optimization

  • Marina Kondratovich
  • Anatoly Zhigljaysky
Conference paper
Part of the Lecture Notes in Statistics book series (LNS, volume 127)

Abstract

Let X be a compact subset of R d and {xl,…,xn} be a sample of random points in X. It is well—known that any properly organized stratified sampling procedure is superior to the independent sampling with respect to the variance of Monte Carlo estimates of integrals of functions in L 2 (X). We prove similar results for some perfomance characteristics important in global optimization. We also demonstrate that the stratified sample with the maximum stratification is optimum, in a suitable sense.

Keywords

Global Optimization Compact Subset Stratify Sample Global Maximum Stochastic Dominance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    A.A. Zhigljaysky Theory of Global Random Search, Kluwer Academic Publishers, Dordrecht, 1991.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • Marina Kondratovich
    • 1
  • Anatoly Zhigljaysky
    • 1
  1. 1.Department of MathematicsUniversity of St.PetersburgSt. PetersburgRussia

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