Multivariate [theta]-generalized normal distributions

Irwin R. Goodman and Samuel Kotz

Journal of Multivariate Analysis, 1973, vol. 3, issue 2, 204-219

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 [theta]'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.

Keywords: Generalized; multivariate; normal; [theta]-matrices; estimation; maximal; entropy; linear; regression; model; Rao-Cramer; bounds (search for similar items in EconPapers)
Date: 1973
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Citations: View citations in EconPapers (6)

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