Multivariate θ-generalized normal distributions |
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Authors: | Irwin R Goodman Samuel Kotz |
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Affiliation: | 1. U.S. Naval Air Development Center, Temple University, Philadelphia, Pennsylvania 19122 USA;2. Department of Mathematics, Temple University, Philadelphia, Pennsylvania 19122 USA |
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Abstract: | A new family of continuous multivariate distributions is introduced, generalizing the canonical form of the multivariate normal distribution. The well-known univariate version of this family, as developed by Box, Tiao and Lund, among others, has proven a valuable tool in Bayesian analysis and robustness studies, as well as serving as a unified model for least θ's and maximum likelihood estimates. The purpose of the family introduced here is to extend, to a degree of generality which will permit practical applications, the useful role played by the univariate family to a multidimensional setting. |
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Keywords: | 60E10 Generalized multivariate normal θ-matrices estimation maximal entropy linear regression model Rao-Cramér bounds |
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