A monte-carlo approach to error propagation

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Abstract

A Monte-Carlo approach to error propagation from input parameters of known variance (and covariance if available) properties through an arbitrarily complicated analytic or numerical transformation to output parameters is discussed. A simple random-number generator for a rectangular distribution function is shown to provide an econimical and fairly efficient means of simulating the effects of using a normal distribution function.

References (12)

  • J.F. Ogilvie

    Comput. Phys. Commun.

    (1983)
  • J.F. Ogilvie et al.

    Comput. Chem.

    (1981)
  • J.F. Ogilvie et al.

    J. Mol. Spectrosc.

    (1976)
  • R.H. Tipping et al.

    J. Mol. Spectrosc.

    (1982)
  • R.P. Brent

    Commun. A.C.M.

    (1974)
  • A.A. Clifford
    (1973)
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1

Present address: Department of Physics, University of Albama, AL 35486-1921, U.S.A.

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