It is well known that the maximum likelihood estimates (MLEs) of a multivariate normal distribution from incomplete data with a monotone pattern have closed-form expressions and that the MLEs from incomplete data with a general missing-data pattern can be obtained using the Expectation-Maximization
ML Characterization of the Multivariate Normal Distribution
โ Scribed by W. Stadje
- Publisher
- Elsevier Science
- Year
- 1993
- Tongue
- English
- Weight
- 232 KB
- Volume
- 46
- Category
- Article
- ISSN
- 0047-259X
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โฆ Synopsis
It is a well-known result (which can be traced back to Gauss) that the only translation family of probability densities on (\mathbb{R}) for which the arithmetic mean is a maximum likelihood estimate of the translation parameter originates from the normal density. We generalize this characterization of the normal density to multivariate translation families. ic 1993 Academic Press, Inc.
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