Quarterly of Applied Mathematics

Quarterly of Applied Mathematics

Online ISSN 1552-4485; Print ISSN 0033-569X

   
 
 

 

An adaptive algorithm to accelerate multi-parameter Monte Carlo computations


Authors: Donald L. Hitzl and Frank Zele
Journal: Quart. Appl. Math. 39 (1981), 329-340
DOI: https://doi.org/10.1090/qam/99623
MathSciNet review: QAM99623
Full-text PDF Free Access

Abstract | References | Additional Information

Abstract: Estimator expansions in terms of orthonormal Hermite polynomials show particular promise for variance reduction in Monte Carlo computer simulations. This paper briefly describes some new adaptive refinements to the basic variance reduction procedure so that the acceleration towards convergence of multi-parameter Monte Carlo computations is further improved. Simulation results using the adaptive algorithm are presented for a five-parameter model problem.


References [Enhancements On Off] (What's this?)

  • [1] W. Freiberger and U. Grenander, A short course in computational probability and statistics, Springer-Verlag, New York, 1971 MR 0478422
  • [2] A. J. Chorin, Hermite expansions in Monte Carlo computation, J. Comp. Phys. 8, 472-482 (1971) MR 0297092
  • [3] F. H. Maltz and D. L. Hitzl, Variance reduction in Monte Carlo computations using multi-dimensional Hermite polynomials, J. Comp. Phys. 32, 345-376 (1979) MR 544556
  • [4] F. H. Maltz and D. L. Hitzl, Nonlinear adaptive estimation procedures for increasing the efficiency in Monte Carlo computations, J. Guid. and Cont. 3, 251-256 (1980) MR 575583
  • [5] D. L. Hitzl and F. H. Maltz, Adaptive estimation procedures for multi-parameter Monte Carlo computations, J. Comp. Phys. 37, 218-241 (1980) MR 586442
  • [6] F. Zele and D. L. Hitzl, Advanced Monte Carlo software for IAP applications, LMSC technical report D676956, 1979


Additional Information

DOI: https://doi.org/10.1090/qam/99623
Article copyright: © Copyright 1981 American Mathematical Society

American Mathematical Society