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A note on the existence of maximum likelihood estimates for Gaussian-inverted Wishart models

โœ Scribed by N. Le; L. Sun; J.V. Zidek

Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
221 KB
Volume
40
Category
Article
ISSN
0167-7152

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โœฆ Synopsis

We show that a non-identifiability problem can occur when one attempts to estimate the degrees of freedom and the unstructured covariance matrix simultaneously in a Gaussian-inverted Wishart model, using the maximum likelihood approach. However, the EM algorithm may falsely converge to give finite estimates in this case simply because of the convergence criterion used. An alternative approach is proposed to overcome the problem. (~

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A note on admissibility of the maximum likelihood estimator for a bounded normal mean
โœ Manabu Iwasa; Yoshiya Moritani ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 279 KB

In estimating a bounded normal mean, it is known that the maximum likelihood estimator is inadmissible for squared error loss function. In this paper, we discuss the admissibility for other loss functions. We prove that the maximum likelihood estimator is admissible under absolute error loss.