Estimates with asymptotically uniformly minimal d-risk

dc.contributor.author	Zaikin A.
dc.date.accessioned	2020-01-22T20:32:12Z
dc.date.available	2020-01-22T20:32:12Z
dc.date.issued	2019
dc.identifier.issn	0040-585X
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/157924
dc.description.abstract	© 2019 Society for Industrial and Applied Mathematics. The definition of a decision function with asymptotically (n →∞) uniformly minimal d-risk is presented in the framework of the general theory of statistical inference. Using this definition, we prove that the maximum likelihood estimate has asymptotically uniformly minimal d-risk. This extends one result by I. N. Volodin and A. A. Novikov [Theory Probab. Appl., 38 (1994), pp. 118–128] for shrinking priors to the general class of continuous distributions. The proof uses the asymptotic representation of the posterior risk function, as obtained in [A. A. Zaikin, J. Math. Sci. (N.Y.), 229 (2018), pp. 678–697].
dc.relation.ispartofseries	Theory of Probability and its Applications
dc.subject	D-risk
dc.subject	Maximum likelihood estimate
dc.subject	Posterior risk asymptotics
dc.title	Estimates with asymptotically uniformly minimal d-risk
dc.type	Article
dc.relation.ispartofseries-issue	3
dc.relation.ispartofseries-volume	63
dc.collection	Публикации сотрудников КФУ
dc.relation.startpage	500
dc.source.id	SCOPUS0040585X-2019-63-3-SID85064694652

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Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.