Development and comparison of Bayesian and classical statistical methods as applied to randomized weather modification experiments.
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Development and comparison of Bayesian and classical statistical methods as applied to randomized weather modification experiments.

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  • Personal Author:
    Olsen, Anthony R.
  • Corporate Authors:
    Environmental Research Laboratories (U.S.). Weather Modification Program Office.
  • NOAA Program & Office:
    OAR (Oceanic and Atmospheric Research)
  • Description:
    The Experimental Meteorology Laboratory has been conducting randomized dynamic cumulus seeding programs in south Florida to investigate the possible effects of cloud seeding on rainfall. There have been numerous statistical analyses performed under varying assumptions, including non parametric techniques, transformations of data for application of normal theory and the application of Bayesian techniques. However, none of the analyses have presented both a Bayesian, which requires numerous assumptions , and a classical analysis utilizing the same assumptions. This report develops the Bayesian and Classical statistical analyses under similar assumptions concerning the underlying distributions. It is assumed that the basic distribution is a highly skewed gamma distribution and that the treatment effect is multiplicative. Within this framework, two situations are studied. The first assumes that the control, or natural, distribution is completely known. The second assumes only that the shape parameter of the gamma distribution is known. For each of these, Bayesian and Classical statistical methods are developed and compared. It is shown that the methods give the same numerical results when an improper diffuse prior 1/0 is used for the seeding effect parameter in the first situation and, similarly, when the additional improper prior 1/p is used for the scale parameter in the control distribution for the second situation
  • Keywords:
  • Series:
    NOAA technical memorandum ERL WMPO ; 10
  • Document Type:
    Technical Memorandum
  • License:
  • Rights Information:
    CC0 Public Domain
  • Compliance:
    Library
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