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An Efficient and Theoretically Consistent Procedure for Generating Correlated, Non-Normal Random Variables in Simulation Models

Author

Listed:
  • Ramirez, O. A.
  • Boggess, W. G.
  • Moss, C. B.

Abstract

In recent years, simulation has become an important methodology for applied decision analysis under uncertainty. A typical simulation effort requires generating a set of possibly correlated and non-normal random variables, using information regarding their underlying joint probability density function contained in a presumably random sample. A few techniques have been suggested to accomplish this task, but most have not met ·the requirement of being correct and efficient from the statistical point of view. This study proposes a multivariate hyperbolic sine probability density function as a basis to develop an efficient and theoretically consistent approach for generating correlated, non-normal random variables.

Suggested Citation

  • Ramirez, O. A. & Boggess, W. G. & Moss, C. B., 1990. "An Efficient and Theoretically Consistent Procedure for Generating Correlated, Non-Normal Random Variables in Simulation Models," 1990 Annual meeting, August 5-8, Vancouver, Canada 271052, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea90:271052
    DOI: 10.22004/ag.econ.271052
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    References listed on IDEAS

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    1. King, Robert P., 1979. "Operational Techniques for Applied Decision Analysis Under Uncertainty," AAEA Fellows - Dissertations and Theses, Agricultural and Applied Economics Association, number 181951, December.
    2. Anderson, Jock R., 1974. "Simulation: Methodology and Application in Agricultural Economics," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 42(01), pages 1-53, March.
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    Cited by:

    1. Moss, Charles B. & Shonkwiler, J. S., 1991. "Modeling Yield With Stochastic Trend And Nonnormal Errors," 1991 Annual Meeting, August 4-7, Manhattan, Kansas 271165, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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