Abstract
A procedure is developed that enables the encoding of a subjectiven-dimensional joint normal probability density function through the assessment of its marginal means and variances andn(n−1)/2 conditional means. The new method is based on the theory of conjugate directions for quadratic forms, and it exploits the fact that normal distributions have quadratic equal-likelihood surfaces. Unlike previous approaches, this new method enables easy detection and resolution of inconsistencies in the assessments that could lead to an indefinite estimate of the covariance matrix.
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Communicated by R. A. Howard
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Oren, S.S. A conjugate directions method for subjective assessment of normal distributions. J Optim Theory Appl 33, 25–36 (1981). https://doi.org/10.1007/BF00935174
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DOI: https://doi.org/10.1007/BF00935174