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    Author(s): P. J. Ince; J. Buongiorno
    Date: 1991
    Source: Proceedings of the 1991 Symposium on Systems Analysis in Forest Resources : March 3-6, 1991, Charleston, South Carolina. Asheville, NC : Southeastern Forest Experiment Station, 1991. General technical report SE ; 74.:p. 143-150 : ill.
    Publication Series: General Technical Report (GTR)
    Station: Forest Products Laboratory
    PDF: View PDF  (87.0 MB)

    Description

    In many applications of Monte Carlo simulation in forestry or forest products, it may be known that some variables are correlated. However, for simplicity, in most simulations it has been assumed that random variables are independently distributed. This report describes an alternative Monte Carlo simulation technique for subjectively assesed multivariate normal distributions. The method requires subjective estimates of the 99-percent confidence interval for the expected value of each random variable and of the partial correlations among the variables. The technique can be used to generate pseudorandom data corresponding to the specified distribution. If the subjective parameters do not yield a positive definite covariance matrix, the technique determines minimal adjustments in variance assumptions needed to restore positive definiteness. The method is validated and then applied to a capital investment simulation for a new papermaking technology. In that example, with ten correlated random variables, no significant difference was detected between multivariate stochastic simulation results and results that ignored the correlation. In general, however, data correlation could affect results of stochastic simulation, as shown by the validation results.

    Publication Notes

    • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

    Citation

    Ince, P. J.; Buongiorno, J. 1991. Multivariate stochastic simulation with subjective multivariate normal distributions. Proceedings of the 1991 Symposium on Systems Analysis in Forest Resources : March 3-6, 1991, Charleston, South Carolina. Asheville, NC : Southeastern Forest Experiment Station, 1991. General technical report SE ; 74.:p. 143-150 : ill.

    Keywords

    Forestry, Forest products industries, Monte Carlo method, Stochastic processes, Mathematical models, Statistical analysis

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