Exact propagation of uncertainties in multiplicative models |
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Authors: | Phongtape Wiwatanadate H Gregg Claycamp |
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Institution: | 1. Department of Environmental and Occupational Health , University of Pittsburgh , 260 Kappa Drive, Pittsburgh, PA, 15238 Phone: (412) 967–6524 Fax: (412) 967–6524;2. Department of Community Medicine, Faculty of Medicine , Chiang Mai University , Chiang Mai, 50200, Thailand Phone: 66–53–945472 to 4 Fax: 66–53–945472 to 4;3. Department of Environmental and Occupational Health , University of Pittsburgh , 260 Kappa Drive, Pittsburgh, PA, 15238 Phone: (412) 967–6524 Fax: (412) 967–6524 |
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Abstract: | Propagation of uncertainties has been widely accepted as an integral component in health risk assessments. Historically, the approximations based on Taylor series expansions have been applied, but they are valid only when the model is linear or the coefficients of variation are small. Another approximation approach is Monte Carlo analysis. It is simpler and more practical for risk management but may become cumbersome if the model involves many variables containing large uncertainties. Recently, the exact log transform technique has been proposed for multiplicative models with lognormal uncertainties. The purpose of this paper is to present a novel exact analytical method as a complementary approach to simulation for general multiplicative models with independent variables, without a constraint on the types of uncertainty distributions. It also provides good estimates of the mean and variance of highly skewed distributions, determination of their existence, and verification of sufficient simulation sample size for simulation method. Two case examples are given to demonstrate the applications. |
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Keywords: | Propagation of uncertainties uncertainty analysis multiplicative model probability Monte Carlo analysis |
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