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Concentration inequality of maximum likelihood estimator

โœ Scribed by Yu Miao

Publisher
Elsevier Science
Year
2010
Tongue
English
Weight
246 KB
Volume
23
Category
Article
ISSN
0893-9659

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โœฆ Synopsis

For a sequence of independent and identically distributed random variables (r.v.) valued in some metric space (E, d), we obtain a sharp concentration inequality of the maximum likelihood estimator under some standard concavity condition.

๐Ÿ“œ SIMILAR VOLUMES

An elementary derivation of the maximum
An elementary derivation of the maximum likelihood estimator of the covariance matrix, and an illustrative determinant inequality
โœ Seppo Karrila; Tapio Westerlund ๐Ÿ“‚ Article ๐Ÿ“… 1991 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 141 KB

The unique maximum likelihood estimate of the covariance matrix of normally distributed random vectors is derived by use of elementary linear algebra leading to simple scalar equations. In addition the application of a determinant inequality, also derived here, shows that a standard "derivation" of