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Error Propagation for Large Errors

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  • Fritz A. Seiler

Abstract

An essential facet of a risk assessment is the correct evaluation of uncertainties inherent in the numerical results. If the calculation is based on an explicit algebraic expression, an analytical treatment of error propagation is possible, usually as an approximation valid for small errors. In many instances, however, the errors are large and uncertain. It is the purpose of this paper to demonstrate that despite large errors, an analytical treatment is possible in many instances. These cases can be identified by an analysis of the algebraic structure and a detailed examination of the errors in input parameters and mathematical models. From a general formula, explicit formulas for some simple algebraic structures that occur often in risk assessments are derived and applied to practical problems.

Suggested Citation

  • Fritz A. Seiler, 1987. "Error Propagation for Large Errors," Risk Analysis, John Wiley & Sons, vol. 7(4), pages 509-518, December.
    • Handle: RePEc:wly:riskan:v:7:y:1987:i:4:p:509-518
    DOI: 10.1111/j.1539-6924.1987.tb00487.x
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    References listed on IDEAS

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    1. David C. Cox & Paul Baybutt, 1981. "Methods for Uncertainty Analysis: A Comparative Survey," Risk Analysis, John Wiley & Sons, vol. 1(4), pages 251-258, December.
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    Cited by:

    1. Mario Situm, 2021. "Determination of expected cost of equity with the CAPM: Theoretical extension using the law of error propagation," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(1), pages 77-84, January.
    2. Andrew E. Smith & P. Barry Ryan & John S. Evans, 1992. "The Effect of Neglecting Correlations When Propagating Uncertainty and Estimating the Population Distribution of Risk," Risk Analysis, John Wiley & Sons, vol. 12(4), pages 467-474, December.
    3. Fritz A. Seiler & Joseph L. Alvarez, 1996. "On the Selection of Distributions for Stochastic Variables," Risk Analysis, John Wiley & Sons, vol. 16(1), pages 5-18, February.

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