Effect of initial seed and number of samples on simple-random and Latin-Hypercube Monte Carlo probabilities (confidence interval considerations)

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In order to devise an algorithm for autonomously terminating Monte Carlo sampling when sufficiently small and reliable confidence intervals (CI) are achieved on calculated probabilities, the behavior of CI estimators must be characterized. This knowledge is also required in comparing the accuracy of other probability estimation techniques to Monte Carlo results. Based on 100 trials in a hypothesis test, estimated 95% CI from classical approximate CI theory are empirically examined to determine if they behave as true 95% CI over spectrums of probabilities (population proportions) ranging from 0.001 to 0.99 in a test problem. Tests are conducted for population sizes ... continued below

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6 p.

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ROMERO,VICENTE J. May 4, 2000.

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  • Sandia National Laboratories
    Publisher Info: Sandia National Labs., Albuquerque, NM, and Livermore, CA (United States)
    Place of Publication: Albuquerque, New Mexico

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In order to devise an algorithm for autonomously terminating Monte Carlo sampling when sufficiently small and reliable confidence intervals (CI) are achieved on calculated probabilities, the behavior of CI estimators must be characterized. This knowledge is also required in comparing the accuracy of other probability estimation techniques to Monte Carlo results. Based on 100 trials in a hypothesis test, estimated 95% CI from classical approximate CI theory are empirically examined to determine if they behave as true 95% CI over spectrums of probabilities (population proportions) ranging from 0.001 to 0.99 in a test problem. Tests are conducted for population sizes of 500 and 10,000 samples where applicable. Significant differences between true and estimated 95% CI are found to occur at probabilities between 0.1 and 0.9, such that estimated 95% CI can be rejected as not being true 95% CI at less than a 40% chance of incorrect rejection. With regard to Latin Hypercube sampling (LHS), though no general theory has been verified for accurately estimating LHS CI, recent numerical experiments on the test problem have found LHS to be conservatively over an order of magnitude more efficient than SRS for similar sized CI on probabilities ranging between 0.25 and 0.75. The efficiency advantage of LHS vanishes, however, as the probability extremes of 0 and 1 are approached.

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6 p.

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OSTI as DE00756096

Medium: P; Size: 6 pages

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  • 8th ASCE Specialty Conference on Probabilistic Mechanics and Structural Reliability, South Bend, IN (US), 07/24/2000--07/26/2000

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  • Report No.: SAND2000-1131C
  • Grant Number: AC04-94AL85000
  • Office of Scientific & Technical Information Report Number: 756096
  • Archival Resource Key: ark:/67531/metadc708960

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  • May 4, 2000

Added to The UNT Digital Library

  • Sept. 12, 2015, 6:31 a.m.

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  • April 11, 2017, 12:59 p.m.

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ROMERO,VICENTE J. Effect of initial seed and number of samples on simple-random and Latin-Hypercube Monte Carlo probabilities (confidence interval considerations), article, May 4, 2000; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc708960/: accessed November 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.